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Supply Chain Inventory Management and Value of Shared Information
Abstract
In traditional supply chain inventory management, orders are the only information firms exchange, but information technology now allows firms to share demand and inventory data quickly and inexpensively. We study the value of sharing these data in a model with one supplier, N identical retailers, and stationary stochastic consumer demand. There are inventory holding costs and back-order penalty costs. We compare a traditional information policy that does not use shared information with a full information policy that does exploit shared information. In a numerical study we find that supply chain costs are 2.2% lower on average with the full information policy than with the traditional information policy, and the maximum difference is 12.1%. We also develop a simulation-based lower bound over all feasible policies. The cost difference between the traditional information policy and the lower bound is an upper bound on the value of information sharing: In the same study, that difference is 3.4% on average, and no more than 13.8%. We contrast the value of information sharing with two other benefits of information technology, faster and cheaper order processing, which lead to shorter lead times and smaller batch sizes, respectively. In our sample, cutting lead times nearly in half reduces costs by 21% on average, and cutting batches in half reduces costs by 22% on average. For the settings we study, we conclude that implementing information technology to accelerate and smooth the physical flow of goods through a supply chain is significantly more valuable than using information technology to expand the flow of information.
... Research focusing on Marcao residents by Zhang et al. [3] revealed that 90% of respondents were willing to purchase EVs, with 57% ready to pay for them. Xu et al. [4] discovered that 77.60% of respondents were prepared to pay extra for agricultural products with Sustainability 2024, 16, 9056 2 of 15 carbon labels, indicating that awareness of low-carbon practices significantly influences the acceptance of carbon-labeled products. ...
... Chen et al. [13] and Aviv [14] provided extensive literature reviews. Most of the existing research has analyzed savings from sharing information about inventory and replenishment [15,16] or pricing [17][18][19]. Lee, So, and Tang [20] highlighted the high value of demand information sharing, especially when demands are significantly correlated over time. ...
In view of the crucial role of consumer data concerning low-carbon preferences, a low-carbon supply chain was established, encompassing one manufacturer and one retailer. Both entities employed technological tools to predict consumer demand. This study assessed the profitability of supply chain participants under two strategies, “make-to-order” and “make-to-stock”, considering scenarios with and without demand forecast sharing information. Furthermore, we investigated how factors such as demand variability, forecast biases from the manufacturer and the retailer, and the forecast correlation coefficient affect the performance of the supply chain and the benefits of sharing information. Our findings indicate that the strategies of supply chain members remain unaffected by the chosen production models and that information sharing proves advantageous for the manufacturer and the retailer. Especially for manufacturers, profits in a “make-to-order” scenario surpass those in a “make-to-stock” scenario. Our numerical analysis showed that profits for the manufacturer and the retailer were consistently higher in scenarios where information was shared than in cases where it was not for “make-to-order” and “make-to-stock” strategies.
... A related research stream is information sharing in the supply chain, where the focus is on information sharing between partners to improve supply chain efficiency (e.g. 15,38,42,55,22). For example, in the case of a Managed Security Service Provider (MSSP), providers learn from servicing one firm and this learning naturally accrues to other client firms [16]. ...
... Proof: This is straightforward from the partial derivatives of equilibrium firm investment in (11) and (15), and equilibrium firm profit in (12) and (16), for common and different providers, respectively, with respect to the corresponding parameters. □ From Proposition 1(a), firms invest more if marginal profit before investment is high. ...
Digital supply chains are increasingly interconnected and vulnerable to disruption, causing service interruptions impacting many firms and their customers. Combating threats to the digital supply chain is the top challenge for leaders in most supply chain industries, demonstrated by the tacit approval of nation-states for cyber-attacks on corporate supply chains to disrupt downstream firms.
Disruptions to digital supply chains are not new. In April 2019, hundreds of flights in the United States were delayed when a critical service provider, AeroData, had a computer systems failure. AeroData delivers flight planning services to many airlines including Southwest, United, American, and Delta. All flight operations for AeroData’s over 100 clients simultaneously ceased and thousands of customers were stranded at airports across the country. In an increasingly connected business environment, competitors may be simultaneously disrupted due to a common service provider, impacting all affected firms’ demand.
The synchronization of disruptions for firms that use a common service provider has implications for service provider choice and investment. We use a two-stage game to model how a firm’s customer demand is impacted by disruptions at a service provider, and how this subsequently affects the firms’ choices in managing service provider risk. Considering downstream demand effects from upstream service disruptions, the contribution of this paper is the examination of how risk synchronization impacts provider choice decisions and profits. In addition, we illustrate how these choices impact upstream industry concentration.
... Consequently, inter-organizational data sharing is necessary to perform fundamental coordinating activities in supply chains in all their individual parts (e.g., resource collection, assembly) (Cachon & Fisher 2000;Luo et al. 2013;Stefansson 2002;Wang et al. 2021). It impacts upstream and downstream business processes of supply chain participants, such as production, and is a known strategy to mitigate the bullwhip effect, which occurs when fluctuations in production or orders outweigh inventory and variations in consumer demands impact a supplier's production (Lee et al. 1997;Wang & Disney 2016). ...
... Potential reasons for this narrow scope most likely originate in prevailing fears of misconduct or breaches of confidentiality by data users (Kuo et al. 2014). Cachon & Fisher (2000p. 1033) already explored the value of shared data between "traditional information sharing" restricted to only orders and "full information sharing" with a range of benefits (e.g., improving order quantity decisions or allocating batches based on inventory positions). ...
Industrial data ecosystems are inter-organizational forms of cooperation emerging around sharing data. They arise from a
digital infrastructure, giving data providers and data users a platform to share and (re-)use data. Data spaces are among the
digital infrastructures frequently associated with data ecosystems, as they supply a shared digital space for its participants
to share data in a sovereign way. Data spaces aim to close a gap in the digital infrastructure landscape, addressing concerns
of organizations when sharing data, such as data misappropriation or a lack of control of shared data. They do this by
implementing data sovereignty—typically through Usage Control Policies—that give data providers the means to formalize semantically and technically how data users are allowed to use their data. In this fundamentals article, we address the
following issues: (1) contextualizing and demarcating data spaces and data ecosystems, (2) systematizing data spaces in the
research and policy landscape, and (3) elaborating on a research agenda for Information Systems (IS) research.
... Given the abundance of components in some of these products, there is a felt need to organize production and manufacturing processes. Internal manufacturing of all components presents significant challenges, the most crucial being the organization of human resources and the creation of additional resources during market and demand changes (Cachon & Fisher, 2000). ...
... Shareholder value improves through maximizing company value. Laínez and colleagues consider shareholder value to depend on three factors: net income, invested capital, and debts (Cachon & Fisher, 2000;Gunasekaran et al., 2004). ...
Objective: The purpose of this research was to investigate the supply chain capabilities in the food industries by using indicators of competitive advantage, financial performance, and shareholder value to improve supply chain capabilities and ultimately design an appropriate structural model. Methodology: The present study is quantitative and descriptive-analytical in nature. The population of the study includes employees and experts in the food manufacturing industries, totaling 500 individuals. To determine the minimum sample size required, Morgan's table for limited populations was used, and ultimately, 217 completed questionnaires were returned and analyzed. The data collection tool was a researcher-made questionnaire. Data analysis was performed using structural equations and AMOS software. Findings: The results indicated significant relationships and components of the presented model. Factor analysis results showed that the paths and causal relationships between external and internal constructs in the structural model were confirmed with 95 percent probability. Conclusion: In general, initiatives based on cost reduction and productivity improvement are easier than others. For example, if an initiative focusing on reducing inventory levels leads to achieving previous sales levels, the benefits of this initiative are easily measurable. However, long-term growth requires an increase in revenue, and managers need to focus on all four methods mentioned above to enhance company value.
... Given the scarcity of available data regarding the lead time of suppliers, we randomly sample values for ′′ from a uniform distribution within the 1 to 5-day range. A similar range of lead time previously employed in [117]. In this study, we have sourced the values of , , and from various sources, including [118][119][120]. ...
Electric vertical takeoff and landing (eVTOL) aircraft manufacturers await numerous pre-orders for eVTOLs and expect demand for such advanced air mobility (AAM) aircraft to rise dramatically soon. However, eVTOL manufacturers (EMs) cannot commence mass production of commercial eVTOLs due to a lack of supply chain planning for eVTOL manufacturing. The eVTOL supply chain differs from traditional ones due to stringent quality standards and limited suppliers for eVTOL parts, shortages in skilled labor and machinery, and contract renegotiations with major aerospace suppliers. The emerging AAM aircraft market introduces uncertainties in supplier pricing and capacities, eVTOL manufacturing costs, and eVTOL demand, further compounding the supply chain planning challenges for EMs. Despite this critical need, no study has been conducted to develop a comprehensive supply chain planning model for EMs. To address this research gap, we propose a stochastic optimization model for integrated supply chain planning of EMs while maximizing their operating profits under the abovementioned uncertainties. We conduct various numerical cases to analyze the impact of 1) endogenous eVTOL demand influenced by the quality of eVTOLs, 2) supply chain disruptions caused by geopolitical conflicts and resource scarcity, and 3) high-volume eVTOL demand similar to that experienced by automotive manufacturers, on EM supply chain planning. The results indicate that our proposed model is adaptable in all cases and outperforms established benchmark stochastic models. The findings suggest that EMs can commence mass eVTOL production with our model, enabling them to make optimal decisions and profits even under potential disruptions.
... Some authors noted that traditionally, firms only exchange order information, but advancements in information technology now enable the quick and inexpensive sharing of demand and inventory data. Numerical studies demonstrated that average supply chain costs were lower when shared information was implemented [3]. These findings were • A supply chain planning model that takes into account supply and inventory levels; • Short-term planning of distribution process networks; • The combination of inventory planning with inventory policy, which enables better operational decisions (e.g., minimizing ordering, holding, and transportation costs) for supply chain managers. ...
Inventory supply chain planning involves determining the quantity of products to be transported among entities within a specified planning horizon. Often, inventory levels are reviewed at set intervals: (1) Background: In this paper, periodic review (s,S) policy is used to optimize inventories from an integrated perspective of inventory management across the supply chain. The decision to place an order and the order quantity are based on the inventory level at the review time. If the inventory falls below a certain level (s), an order is placed to replenish it to a target level (S); (2) Methods: The planning model is implemented using a mixed integer linear programming model. It determines the inventory levels, supply levels and the (s) and (S) levels for each entity, as well as the flow of products between them. To test the model, a case study is conducted to demonstrate its applicability; (3) Results: The experimental data confirm the model’s validity, as its behavior aligns with the expectations for a periodic review (s,S) policy; (4) Conclusions: Since a fixed replenishment frequency is mandatory, with no continuous inventory review required, this policy offers simplicity and ease of implementation, making it a practical choice for certain inventory management.
... The expenses of inventory management have an effect on the value of inventory via direct means [16]. ...
For competitiveness provisions in today's intense industrial settings, the collection and management of materials data and inventory are critical for organisational operations and goal attainment. This paper aims to investigate the shift from conventional practices with reference to manual processes to contemporary automated technological tools regards inventory management with regard to barcoding, RFID, IoT, and predictive analysis. It enhances accuracy and real-time information monitoring and consequently would improve decision-making. However, an innovative issue such as data accuracy, integration problems, and large infrastructure costs are some of the barriers that are remaining paramount. The paper also reviews the number of inventory management methods known as Just-In-Time (JIT), Vendor-Managed Inventory (VMI) and ABC classification methods and attempts to discuss how those work in practice. The current trends that are still new to company practices include AI, the use of blockchain technology, robotics as well as cloud computing, as so many practices which can help to bring about changes to the way that inventory is managed. Key themes of the study focus on the impact of the technologies on cost reduction, supply chain dexterity, and efficiency improvement. The study attempts to provide practical insights for enhancing inventory management procedures and gaining a competitive edge in the changing market by evaluating the efficacy of various technologies and tactics.
... Inventory and Capacity Buffer Shock absorption against disruptions; time to adjust supply chains and minimize production impact [12] S3 Ecosystem Partnership Collaboration and knowledge sharing; early disruption identification and risk mitigation; reduced lead times and improved responsiveness [6,13] ...
... In this vein, operations research models have shown that inventory decisions should be coordinated across the supply chain because they have interactive effects on performance (Cachon & Fisher, 2000). Dong et al. (2018) argue that, regardless of the proximity between buyers and suppliers, upstream and downstream inventories are substitutes; if buyers do not hold enough inventory, suppliers must hold inventory. ...
This study examines how inventory slack at first‐ and second‐tier suppliers influences buyer performance following an upstream disruption event. We analyze secondary data from buyer, first‐tier, and second‐tier triads impacted at their upper end by the 2011 Great East Japan Earthquake. By matching buyers in affected triads with similar, largely unaffected firms, we assess post‐event performance in relation to triad inventory slack. Results show: (a) inventory slack at the first and second tiers supports buyer performance after the disruption; (b) first‐tier inventory slack has a greater impact; (c) buyers with less inventory slack can extract more value from their chains' inventories compared to those with more slack; and (d) first‐tier suppliers occupy a pivotal role in bridging the second‐tier inventories to the buyer. When competition for the first‐tier intensifies, the benefits of having first‐ and second‐tier inventory slack diminish for the buyer. A central contribution of this study is to highlight the importance of resources controlled by chain members with indirect links to the buyer and the bridging role of first‐tier suppliers. These insights suggest that for effective risk management, both direct and indirect supply chain resources and their interactions need consideration. Practically, these findings should guide supplier selection, risk management, and investments in supply chain visibility.
... Consequently, network centrality in the supply chain can manage demand variability, inventory levels, and production schedules, resulting in more synchronized for supply chain operations. By utilizing the information advantage, enterprises can negotiate better terms with upstream and downstream enterprises, promote the service level, enhance the efficiency of the supply chain [48], and sustainable development [49]. ...
Mergers and acquisitions (M&As) are key drivers for resource integration and the operational efficiency of enterprises. Companies that hold central positions within supply chains may leverage their strategic location to reduce information asymmetry, enhancing their ability to engage in sustainable activities. However, research on the role of supply chain network centrality in M&A decisions remains underexplored. This study aims to empirically examine whether and how centrality in supply chain networks enhances the likelihood and success of M&A activities, contributing to both theory and practice in corporate strategy. In particular, we construct a novel measure of firm centrality within the supply chain and utilize panel data from Chinese A-share listed companies spanning 2008 to 2021. Our findings reveal that the central position of supply chain networks promotes the probability and frequency of mergers and acquisitions. Mechanism analysis reveals that gaining information advantages and relieving financial constraints are two key channels through which the supply chain network promotes mergers and acquisitions. Furthermore, the effects are more pronounced for firms with non-state ownership, with closer proximity to customers or suppliers, with higher operational risk, and with growth and decline phases. A series of robustness tests support these results, including alternative measures, alternative estimating methods, and sub-sample tests. Moreover, central supply chain companies exhibit better long-term financial performance following mergers and acquisitions. This paper enriches our understanding of the roles of supply chain networks in firms’ mergers and acquisitions and holds important practical implications for companies seeking to achieve sustainable and long-term development.
... Many modern technologies, such as IoT, intelligent agents, and robotics, have been adopted to automate various aspects of SCM. These automation functions encompasse a broad range of tasks, from mundane activities like picking and packing orders in warehouses using robotic process automation [Nalgozhina andUskenbayeva, 2024, Ribeiro et al., 2021] to more complex processes such as demand forecasting and planning [Babai et al., 2022], inventory management [Cachon and Fisher, 2000], delivery optimisation [ Mak et al., 2023], and customer services [Cui et al., 2017] through various AI technologies. The use of emerging technologies in SCM automation has been since reviewed in [Hendriksen, 2023, Xu et al., 2021. ...
Recent global disruptions, such as the COVID-19 pandemic and the ongoing geopolitical conflicts, have profoundly exposed vulnerabilities in traditional supply chains, requiring exploration of more resilient alternatives. Among various solution offerings, Autonomous supply chains (ASCs) have emerged as key enablers of increased integration and visibility, enhancing flexibility and resilience in turbulent trade environments through the widespread automation of low level decision making. Although ASC solutions have been discussed and trialled over several years, they still lack well-established theoretical foundations. This paper addresses this research gap by presenting a formal definition of ASC along with its defining characteristics and auxiliary concepts. We propose a layered conceptual framework, called the MIISI model. An illustrative case study focusing on the meat supply chain demonstrates an initial ASC implementation based on this conceptual model. Furthermore, we introduce a seven-level supply chain autonomy reference model, delineating a trajectory towards achieving full supply chain autonomy. Recognising that this work represents an initial endeavour, we emphasise the need for continued exploration in this emerging domain. This work is designed to stimulate further research, both theoretical and technical, and contribute to the continual evolution of ASCs.
... Many modern technologies, such as IoT, intelligent agents, and robotics, have been adopted to automate various aspects of SCM. These automation functions encompasse a broad range of tasks, from mundane activities like picking and packing orders in warehouses using robotic process automation [Nalgozhina andUskenbayeva, 2024, Ribeiro et al., 2021] to more complex processes such as demand forecasting and planning [Babai et al., 2022], inventory management [Cachon and Fisher, 2000], delivery optimisation [ Mak et al., 2023], and customer services [Cui et al., 2017] through various AI technologies. The use of emerging technologies in SCM automation has been since reviewed in [Hendriksen, 2023, Xu et al., 2021. ...
Recent global disruptions, such as the COVID-19 pandemic and the ongoing geopolitical conflicts, have profoundly exposed vulnerabilities in traditional supply chains, requiring exploration of more resilient alternatives. Among various solution offerings, Autonomous supply chains (ASCs) have emerged as key enablers of increased integration and visibility, enhancing flexibility and resilience in turbulent trade environments through the widespread automation of low level decision making. Although ASC solutions have been discussed and trialled over several years, they still lack well-established theoretical foundations. This paper addresses this research gap by presenting a formal definition of ASC along with its defining characteristics and auxiliary concepts. We propose a layered conceptual framework, called the MIISI model. An illustrative case study focusing on the meat supply chain demonstrates an initial ASC implementation based on this conceptual model. Furthermore, we introduce a seven-level supply chain autonomy reference model, delineating a trajectory towards achieving full supply chain autonomy. Recognising that this work represents an initial endeavour, we emphasise the need for continued exploration in this emerging domain. This work is designed to stimulate further research, both theoretical and technical, and contribute to the continual evolution of ASCs.
... Due to the need for businesses to negotiate various cultures, languages, and regulatory frameworks across the globe, supply chain management has become more difficult. [12] These are essential strategies which almost all successful businesses apply, however, there are also other approaches to utilize for maximization of the companies' profit. A few other approaches have been given in the table below. ...
Every company's operations management is its foundation. This is because it is
in charge of several essential corporate operations. My graduation thesis aims
to demonstrate the application of operational management approaches for
organizations located in either developed or developing countries to become
more effective and efficient. The paper indicates the superiority of operation
management techniques and its direct impact on businesses. The expression of
how two developed and two developing nations implement the methods of
operational management to be more profitable and how well one of the
prominent Azerbaijani firms, "Azerbaijan Coca-Cola Bottlers," fulfills
operational management approaches to the production process. In addition, the
strength of the brand against its rivals has been detected by applying SAW
decision-making method. Operation managers might encounter problems
including labor shortages, the inappropriate allocation of production of
distinctive products, strategic planning, logistics delays, and ineffective
communication.
The study will describe how the operations manager defines profitability
orientation through the proper application of operational management
techniques based on corporate standardization, the local economy, employing
a global strategy, and adjusting the local brand.
Key words: operations management, strategy, local market, analysis, product,
developed nations, developing nations, "Azerbaijan Coca-Cola Bottlers,"
... Given the scarcity of available data regarding the lead time of suppliers, we randomly sample values for T″ ij from a uniform distribution within the 1-5-day range. A similar range of lead time previously employed in [119]. In this study, we have sourced the values of x ij , y ij , and L from various sources, including [120][121][122]. ...
Electric vertical takeoff and landing (eVTOL) aircraft manufacturers await numerous pre-orders for eVTOLs and expect demand for such advanced air mobility (AAM) aircraft to rise dramatically soon. However, eVTOL manufacturers (EMs) cannot commence mass production of commercial eVTOLs due to a lack of supply chain planning for eVTOL manufacturing. The eVTOL supply chain differs from traditional ones due to stringent quality standards and limited suppliers for eVTOL parts, shortages in skilled labor and machinery, and contract renegotiations with major aerospace suppliers. The emerging AAM aircraft market introduces uncertainties in supplier pricing and capacities, eVTOL manufacturing costs, and eVTOL demand, further compounding the supply chain planning challenges for EMs. Despite this critical need, no study has been conducted to develop a comprehensive supply chain planning model for EMs. To address this research gap, we propose a stochastic optimization model for integrated supply chain planning of EMs while maximizing their operating profits under the abovementioned uncertainties. We conduct various numerical cases to analyze the impact of 1) endogenous eVTOL demand influenced by the quality of eVTOLs, 2) supply chain disruptions caused by geopolitical conflicts and resource scarcity, and 3) high-volume eVTOL demand similar to that experienced by automotive manufacturers, on EM supply chain planning. The results indicate that our proposed model is adaptable in all cases and outperforms established benchmark stochastic models. The findings suggest that EMs can commence mass eVTOL production with our model, enabling them to make optimal decisions and profits even under potential disruptions.
... They include advanced communication tools and better coordination among supply chain partners, leading to faster decision-making and responsiveness (Christopher & Towill, 2012). Innovations in forecasting and demand planning further optimize inventory levels, reducing holding costs and enhancing supply chain efficiency (Cachon & Fisher, 2020). ...
Effective inventory management techniques are crucial for optimizing the flow of goods across the supply chain. This study aims to determine the moderating effect of process innovation on the relationship between inventory management techniques and supply chain efficiency. A survey method was used in this study. The data collected was cross-sectional, meaning it was gathered at a single point in time. There is a strong positive effect of supplier relationship management on supply performance. Additionally, employee commitment positively and significantly affects supply performance. However, the effect of employee commitment on the relationship between supplier relationship management and supply performance is not statistically significant. When effectively implemented, inventory management techniques can be seen as unique resources specific to an organization. This study aims to contribute to the existing body of knowledge by providing empirical evidence on the interdependence of inventory management techniques, process innovation, and supply chain efficiency.
... Potentially, that could be the source for data sovereignty pitfalls, as getting insights into generic production portfolios of n-th tier suppliers might reveal information about other customers. Yet, if customers can observe information, they gain critical transparency that potentially aggravates bullwhip effects (Cachon and Fisher 2000;Lee et al. 1997Lee et al. , 2000. ...
Car manufacturers and suppliers in the Automotive industry increasingly face the issue of optimization of highly complex supply chains that need to accommodate each customer's precise demands, requiring a vast array of parts and information to be available at the right place and at the right time. This involves data sharing between organizations, which is hindered by various issues, such as fear of data misappropriation by the data receiver or the involuntary disclosure of business secrets. The paper proposes design principles for a novel type of Inter-Organizational Information System, which addresses these challenges through the technical implementation of data sovereignty. The study reports on an Action Design Research study in the Automotive industry between a car manufacturer and a 1st-tier supplier. It contributes (a) design requirements, (b) design features, (c) an instantiation, and (d) design principles for this type of data sovereign inter-organizational information system.
... The topic of information sharing among supply chain members has received considerable attention by OM scholars. The first wave of research concentrated on understanding the value of information sharing and the way information sharing can assist in lowering costs related to inventory holding, mismatch between supply and demand and alleviating the adverse consequences of the bullwhip effect (Chen 1998, Cachon and Fisher 2000, Lee and Whang 2000. For extensive surveys of these issues we refer the reader to Chen (2003) and for a more recent survey by Ha and Tang (2017). ...
... Dogru et al. (2004) and Dogru (2006) conduct extensive numerical studies to quantify the effect of the balance assumption on the performance of the system. Other papers using this assumption include, e.g., Kumar et al. (1995), Bollapragada et al. (1998), Cachon and Fisher (2000), Aviv and Federgruen (2001), Özer (2003). ...
In this paper, we consider a two-echelon distribution system with dual delivery modes for regional and forward distribution centers (RDC and FDCs). The expedited mode provides a shorter lead time than the regular mode but has a higher unit ordering cost. As the optimal ordering policy for a distribution system with dual delivery modes is unknown, we propose an echelon dual-index policy which is a natural extension of the dual-index policy and echelon base-stock policy that have been proved to be near-optimal/optimal for the single-echelon dual-sourcing system and the multi-echelon serial system, respectively. In addition, we provide different run out rationing policies to guarantee the system’s operation. Based on the system dynamics, we establish the evaluation method for the long-run average total cost, and to accelerate the optimization of the policy parameters, we develop a heuristic algorithm to obtain approximate solutions. Our proposed algorithm is proven efficient in extensive numerical studies compared to the full enumeration. Besides, we also evaluate the performance of different rationing policies and investigate the value of dual delivery modes by comparing four distinct systems. Finally, we numerically explore the impact of the demand distribution (correlation and balance) on the system.
... There exists an extensive supply chain management (SCM) literature that investigates the value of exchanging real-time demand and inventory data among supply chain members; see, for example, Chen (1998), Gavirneni et al. (1999), Cachon and Fischer (2000), , Aviv (2001Aviv ( , 2007, Chen (2003), Gaur et al. (2005), Lee 2009, Giloni et al. (2014) and references therein. An early account of the challenges and benefits associated with establishing an information sharing relationship between Wal-Mart and Proctor & Gamble is discussed in Grean and Shaw (2002) (see also Bourland et al. 1996, Lee and Whang 2000, Kulp et al. 2004, Dong et al. 2014. ...
We study the interplay between inventory replenishment policies and information sharing in the context of a two-tier supply chain with a single supplier and a single retailer serving an independent and identically distributed Gaussian market demand. We investigate how the retailer’s inventory policy impacts the supply chain’s cumulative expected long-term average inventory costs [Formula: see text] in two extreme information-sharing cases: (a) full information sharing and (b) no information sharing. To find the retailer’s inventory policy that minimizes [Formula: see text], we formulate an infinite-dimensional optimization problem whose decision variables are the MA([Formula: see text]) coefficients that characterize a stationary ordering policy. Under full information sharing, the optimization problem admits a simple solution and the optimal policy is given by an MA(1) process. On the other hand, to solve the optimization problem under no information sharing, we reformulate the optimization from its time domain formulation to an equivalent z-transform formulation in which the decision variables correspond to elements of the Hardy space H ² . This alternative representation allows us to use a number of results from H ² theory to compute the optimal value of [Formula: see text] and characterize a sequence of ϵ-optimal inventory policies under some mild technical conditions. By comparing the optimal solution under full information sharing and no information sharing, we derive a number of important practical takeaways. For instance, we show that there is value in information sharing if and only if the retailer’s optimal policy under full information sharing is not invertible with respect to the sequence of demand shocks. Furthermore, we derive a fundamental mathematical identity that reveals the value of information sharing by exploiting the canonical Smirnov–Beurling inner–outer factorization of the retailer’s orders when viewed as an element of H ² . We also show that the value of information sharing can grow unboundedly when the cumulative supply chain costs are dominated by the supplier’s inventory costs.
Funding: R. Caldentey acknowledges the University of Chicago Booth School of Business for financial support.
Supplemental Material: The online appendix is available at https://doi.org/10.1287/moor.2023.008 .
... Crucially, achieving high operational efficiency often requires precise coordination across multiple stages of a firm's production process (Cachon and Fisher, 2000;Gavirneni, 2002) and results from a complex interaction of various firm-specific capabilities (Shah and Ward, 2003;Browning and Heath, 2009). These coordination and interactions are typically tacit and path-dependent, making them challenging for competitors to replicate (Browning and Heath, 2009). ...
Theoretical and empirical evidence point to the ability of political leaders to manipulate economic policies and leverage local firms to elevate their political careers. Despite this, there is limited understanding of how these career incentives impact the operational dynamics of the firms involved. This empirical study delves into this gap, revealing that city leaders with fewer promotional incentives are more inclined to mobilize state-owned enterprises (SOEs) within their jurisdiction to pursue sustainable development, as indicated by heightened corporate operational efficiency. Our analysis further indicates that the career prospects of city leaders significantly influence the operational efficiency of SOEs by driving a shift in focus from rapid growth to sustainable development and firms’ adoption of disruptive technologies. We posit that this increase in operational efficiency not only benefits the SOEs but also generates unique value for stakeholders, resulting in elevated market capitalization and reduced stock price crash risk. Our findings carry direct relevance to the ongoing discourse on political incentives and contribute to operations management research, shedding light on the intricate ways in which the political environment can impact the operational performance of firms.
... Overall, logistics integration empowers companies and their supply chain partners to operate as a cohesive unit, leading to enhanced performance across the entire chain [23]. Numerous studies have highlighted the manifold logistics advantages of sharing information with supply chain partners, particularly in inventory management [24,25]. For instance, Vendor-Managed Inventory (VMI) integration with suppliers has been demonstrated to reduce the bullwhip effect [26]. ...
Logistics is presently undergoing a transformative phase driven by rapid digitalization. This trend has spurred an in-depth exploration of the industry's theoretical potential and practical challenges. This comprehensive review focuses on practical applications, delving deeply into the increasing interest in digital technologies within logistics. The primary objective of this study is to conduct a bibliometric analysis to unravel the growth and academic development of the concept of logistic digitalization. The investigation examines academic literature from the Web of Science database spanning 2020-2024. Using VOS Viewer, an intellectual structure and bibliographic analysis are performed on selected articles. The cluster that concentrates on articles about the Internet of Things (IoT) technology and its impact on the logistics economy (the fourth cluster) is most closely related to the digital theme. The study combines theoretical framework, including Michael Porter's and the Resource-Based View, to illustrate the connections that improve business competitiveness. The examination of investments in digital technology sheds light on the logistics sector's experiences during the years when these investments impact labor productivity. Descriptive analysis results suggest that companies implementing technology can achieve a workforce productivity increase of up to 20%, underscoring the significance of technology investments for enhancing business competitiveness. These findings shed light on how various logistics sub-sectors respond to investments in software and computers and the rate at which these technologies influence labor productivity metrics. These empirical findings substantially reinforce the theoretical framework, providing practical implications and emphasizing the critical necessity for logistics firms to integrate digital technologies into their operational frameworks seamlessly. In conclusion, as the logistics landscape hovers on the brink of a digital revolution, businesses must adeptly navigate and wholeheartedly embrace digital solutions to ensure competitiveness.
... Tedarik zinciri yönetimi, tedarikçiler, üreticiler, distribütörler, perakendeciler ve müşteriler arasındaki ürün ve bilgi akışlarının koordinasyonu ile ilgilidir (Zhao, Xie ve Leung, 2002). Bilgi paylaşımının tedarik zinciri performansını artırabileceği ve işletme maliyetlerini azaltabileceği pek çok tedarik zinciri yöneticisi tarafından kabul görmektedir (La Londe ve Ginter, 2004;Cachon ve Fisher, 2000). Bilgi paylaşım politikasının doğru seçilmesi, tedarik zinciri performansı üzerinde önemli bir etkiye sahiptir (Sohn ve Lim, 2008). ...
Bu çalışmada, Türkiye’de faaliyette bulunan et ve et ürünleri üreten işletmelerin tedarik zinciri stratejilerinin bilgi paylaşımı ve rekabet avantajı üzerindeki etkisi ile bilgi paylaşımı ve rekabet avantajının tedarik zinciri performansı üzerindeki etkisi araştırılmıştır. Ayrıca tedarik zinciri stratejilerinin tedarik zinciri performansı üzerindeki etkisinde bilgi paylaşımı ve rekabet avantajının aracı rolü olup olmadığı da çalışma kapsamında incelenmiştir. Çalışmanın amacı doğrultusunda geliştirilen model ve hipotezlerin test edilmesi için Türkiye’de faaliyet gösteren et ve et ürünleri üreticilerine anket uygulaması yapılmıştır. Uygulama sonrasında 408 geçerli anket elde edilmiştir. Anket uygulaması sonucunda elde edilen veriler SPSS ve AMOS programları aracılığıyla analiz edilmiştir. Yapısal eşitlik analizi sonucunda, yalın ve çevik tedarik zinciri stratejilerinin işletmenin müşteriler ve tedarikçilerle bilgi paylaşımı ile rekabet avantajını etkilediği görülmüştür. Müşterilerle bilgi paylaşımı sadece kaynak performansını etkilerken, tedarikçilerle bilgi paylaşımı hem üretim hem de esneklik performansını etkilemiştir. Rekabet avantajı ise kaynak, üretim ve esneklik performansı üzerinde etkili olmuştur. Aracı etkilerin belirlenmesine yönelik analiz sonuçlarında ise çevik tedarik zinciri stratejisinin kaynak performansı üzerinde müşteriler ve tedarikçilerle bilgi paylaşımının aracı rolü hariç diğer tüm aracı rollerin olduğu görülmüştür.
... The construction industry has witnessed the introduction of multiple inventory and supply chain management (SCM) programs since the late 1980s. For the supply chain to operate well, inventory management is one of the crucial components that call for cooperative effort from a variety of stakeholders [10][11][12]. Numerous studies have been conducted to examine the management of the construction supply chain (CSC) from various angles, including information flow, subcontractor management, intelligent agentbased coordination, value stream analysis, integration, decision support system and optimization tool, and simulation platform [10]. Authorities have implemented environmental restrictions to mitigate the adverse consequences of CSC activities, owing to the construction industry's negative environmental impacts (CSC). ...
The characteristics of supply chains in the construction industry give rise to several information and collaboration system needs, such as system affordability and adaptability. The presence of several companies from a variety of industries in supply chains for the construction industry sets them apart. Information sharing and system integration therefore require cooperation and trust. In the manufacturing industry, a lot of efforts are being made to create tools, technologies, and strategies that would allow supply chain actors to communicate with one another and work together. However, it is more challenging to establish a solid environment for inventory and data management in the construction industry. The Internet and information technology are now being used in the construction industry to strengthen cross-organizational relationships. The employment of these tools in this industry is occasionally hampered by limitations like security worries, a lack of managerial commitment, high costs, and deployment rigidity. Additionally, a dynamic configuration of supply chains is required to integrate with more adaptable business models, increase internationalization, and enhance coordination. For this reason, this study primarily explores the inventory and supply chain tools currently in use in the construction industry and evaluates their functionality from a business and consumer perspective. Other areas of study are based on either inventory management for circular buildings or cross-organizational cooperation, and they include secure data storage, information exchange among stakeholders, and their modification. In the end, it aims to emphasize the key problems with data and inventory management in the construction industry, as well as inform about the potential technology solutions to make a guidance of academic and industry specialists within this study.
... Kulp et al. developed an information model for collaborative decision-making in supply chain management [29], developed an information model for collaborative decision-making in supply chain management. Loch et al. developed a conceptual framework that links information integration programs with manufacturer profitability to enable information integration efforts between manufacturers and retailers [30], and Aviv et al. consider the impact of collaborative retailer-supplier forecasting on performance in supply [31], and the potential benefits of collaborative forecasting partners in the supply chain consisting of manufacturers and retailers [32]. Retailers and suppliers are essential components in the supply chain; Gavirneni et al. explore the benefits when suppliers know different information about retailers [33]. ...
In the context of the development of the new period, the pharmaceutical supply chain market is gradually changing from a seller’s market to a buyer’s market. The closer the pharmaceutical supply chain market is to the consumer, the greater the market’s pricing power, so the market power of the pharmaceutical manufacturer and the retailer has changed, and the change in output and demand has increased accordingly. Since the supply chain is uncertain, there are internal and external risks. Retailers and suppliers can operate and coordinate effectively based on their core strengths, improve their ability to avoid internal and external risks and repair flexibly so that the supply chain is relatively balanced and stable. This paper studies the coordination problem of pharmaceutical supply chain stability from the uncertainty of pharmaceutical supply and market demand, establishes a revenue function, and proposes a collaborative decision-making optimization model of "revenue-sharing + margin" according to the revenue function, and further The optimal value interval is given through numerical analysis to realize the Pareto improvement of both parties. The impacts on the expected returns of suppliers and retailers are investigated through the revenue sharing coefficients and margins, which are numerically verified and discussed through examples. The analysis results show that under the collaborative decision-making of "revenue sharing + margin" in the pharmaceutical supply chain, the coordination of revenue sharing between retailers and suppliers can be optimized by adjusting the revenue sharing coefficient and margin.
Social engineering attacks exploit human behavior to bypass security measures, posing a growing threat in cybersecurity. This paper examines future defenses against these attacks by analyzing recent incidents and common attack vectors like phishing, pretexting, baiting, and tailgating, which leverage psychological manipulation. Key trends include AI and machine learning for real-time detection, and zero-trust architecture for stringent access controls and continuous identity verification. The development of regulatory frameworks and industry standards is also crucial for shaping effective defenses. As technology evolves, so do attack methods, necessitating comprehensive solutions that integrate technological, individual, organizational, and governmental strategies to safeguard society.
Purpose
Eco-innovation products, which means achieving more efficient and responsible use of resources and reducing the detrimental impact on the environment, can win a competitive advantage for the enterprises. But it is not easy to implement due to the high cost of eco-innovative technologies development, the uncertainty of market needs and return risk of investment. Many enterprises seek collaborations from their upstream suppliers to jointly carry out eco-innovation, such as Apple, IBM and Nike. A unique feature of collaboration is that efforts by one party enhance the marginal value of the other party's efforts. However, the collaboration will make the partner know the eco-innovation technology and prompt the partner to encroach the market to sell competitive products by herself. Motivated by this observation, this paper considers the optimal collaboration strategy on eco-innovation between upstream and downstream supply chain member and the optimal encroachment strategy of upstream supplier in a supply chain.
Design/methodology/approach
This paper models a supply chain wherein a supplier provides products or materials for her manufacturer and cooperates with her manufacturer in eco-innovation. Also, the supplier could encroach on the market to sell similar products by herself. Then this paper uses game theory and mathematical modeling to do relative analysis.
Findings
The analysis reveals several interesting insights. First, eco-innovation collaboration makes supplier encroachment no longer only rely on the encroachment cost. The delayed realized eco-innovation efficiency information also plays a vital role. Second, different from previous research, the authors find the manufacturer's preference for supplier encroachment depends on the uncertainty of eco-innovation efficiency and potential market demand. Third, both partial and full encroachment strategies of the supplier can effectively improve the eco-innovation level.
Originality/value
The paper is the first to take the interplay between collaboration and encroachment into account in a supply chain. The results caution enterprises and policymakers to take vertical collaboration and delayed realized information into account in the competitive supply chain before making any operational decisions. Furthermore, the authors propose that governmental intervention aimed at stimulating supplier encroachment in appropriate circumstances can contribute to the improved environmental performance of products.
While close distance to trading partners is often viewed as beneficial to business operations, our study reveals a potential downside. We show that a firm's geographical proximity to its major trading partners is positively correlated with audit fees, which can be explained by an opportunistic narrative: close interactions within the supply chain facilitate misconduct, increasing auditors' engagement risk and concerns. Further analyses suggest that mid‐ and lower‐level employees, rather than top management, are more likely to initiate such misconduct. Overall, our findings highlight the dark side of firm–stakeholder geographical proximity and broaden our understanding of its impact on corporate governance.
We study the interplay between inventory replenishment policies and information sharing in the context of a two-tier supply chain with a single supplier and a single retailer serving an independent and identically distributed Gaussian market demand. We investigate how the retailer’s inventory policy impacts the supply chain’s cumulative expected long-term average inventory costs [Formula: see text] in two extreme information-sharing cases: (a) full information sharing and (b) no information sharing. To find the retailer’s inventory policy that minimizes [Formula: see text], we formulate an infinite-dimensional optimization problem whose decision variables are the MA([Formula: see text]) coefficients that characterize a stationary ordering policy. Under full information sharing, the optimization problem admits a simple solution and the optimal policy is given by an MA(1) process. On the other hand, to solve the optimization problem under no information sharing, we reformulate the optimization from its time domain formulation to an equivalent z-transform formulation in which the decision variables correspond to elements of the Hardy space H ² . This alternative representation allows us to use a number of results from H ² theory to compute the optimal value of [Formula: see text] and characterize a sequence of ϵ-optimal inventory policies under some mild technical conditions. By comparing the optimal solution under full information sharing and no information sharing, we derive a number of important practical takeaways. For instance, we show that there is value in information sharing if and only if the retailer’s optimal policy under full information sharing is not invertible with respect to the sequence of demand shocks. Furthermore, we derive a fundamental mathematical identity that reveals the value of information sharing by exploiting the canonical Smirnov–Beurling inner–outer factorization of the retailer’s orders when viewed as an element of H ² . We also show that the value of information sharing can grow unboundedly when the cumulative supply chain costs are dominated by the supplier’s inventory costs.
Funding: R. Caldentey acknowledges the University of Chicago Booth School of Business for financial support.
Supplemental Material: The online appendix is available at https://doi.org/10.1287/moor.2023.0008 .
This paper builds a game theory model that shows how buying from a competitor affects incentives to invest in innovation.
Problem definition: A fundamental issue faced by operations management researcher relates to striking the right balance between rigor and relevance in their work. Another important aspect of operations management research relates to influencing and positively impacting businesses and society at large. We constantly struggle to achieve these objectives. Methodology/results: This MSOM Fellow forum article discusses key opportunities for increasing the relevance and impact of Operations Management research. In particular, it highlights two major areas: technology enabled operations and society and operations where unique opportunities exist for the field to make lasting contributions to business and society. Managerial implications: It concludes with a menu of approaches to enhance practical impact of our research.
Supply chains consist of a collection of firms acting jointly to design, engineer, manufacture, store, distribute, and market a range of products and services to consumers. These supply chains exhibit varying degrees of integration among the participating firms. There may be little formal integration beyond placing orders, shipping and receiving products, and paying for them. But there may be a variety of activities among the firms to ensure cost-effective, timely, and reliable creation and movement of materials, products, and services needed to meet the end customer’s expectations. In the first chapter, we discuss the forces driving changes to supply chain systems, and then introduce five principles that provide the basis for the design and successful operation a supply chain. We next provide five key observations about supply chain behavior. We emphasize the importance of collaboration among supply chain partners and the linkages between the decisions made at different levels in supply chains. We next review basic deterministic planning models, discuss their assumptions, limitations and flaws, and examine the effects of uncertainty, lead times and other factors on supply chain performance. We then introduce a new paradigm for managing supply chains that addresses the problem of managing uncertainty, which we call the No B/C policy. This policy is discussed in detail in Chapter 5. We end this chapter by illustrating how the five fundamental principles are not always present in one of the world’s most important supply chains, the petroleum supply chain.
In this paper we suggest a novel mechanism for information sharing that allows a retailer to control the amount of shared information, and thus to limit information leakage, while still assisting the supplier to make better‐informed decisions and improve the overall efficiency of the supply chain. The control of the amount of leaked information facilitates information sharing because, absent such control, a retailer may refrain from sharing information due to the concern of information leakage. Specifically, we analyze a supply chain in which a retailer observes Autoregressive Moving Average (ARMA) demand for a single product where all players use the myopic order‐up‐to policy for determining their orders. We introduce a new class of information sharing arrangements, coined partial‐information shock (PaIS) sharing. This new class of information sharing agreements extends the previously studied mechanisms of demand sharing and full‐information shock sharing. We demonstrate that the retailer can construct a PaIS sharing arrangement that allows for an intermediate level of information sharing while simultaneously controlling the amount of leakage. We characterize when one PaIS arrangement will be more valuable to the supplier than another. We conclude with a numerical study that highlights that there does not necessarily need to be a tradeoff between the supplier having a better forecast and the retailer experiencing a higher level of leakage.
The study’s predictor variable was green procurement and its relationship with financial performance and the mediating effect of green purchasing behaviour. It could be said that, green procurement is a component/dimension of sustainable procurement. It is however, recommended that, future researchers must consider investigating the effect of sustainable procurement on firm financial performance. Again, the study conceptualized financial performance as the dependent/predicted variable. However, future studies and researchers are recommended to consider the effect of sustainable procurement on green performance as a predicted variable instead of financial performance. Finally, the current study adopted the manufacturing sector as a case study. the reason was that, it is that sector which predominantly procures goods and materials for further production. Though the study found positive relationship between green procurement financial performance. However, future studies are therefore recommended to conduct a comparative analysis between the manufacturing and service sector on sustainable procurement and its effect on green performance.
Were you ill-prepared for COVID-19’s organizational upheavals and supply chain disruptions? Shardul Phadnis and Paul Schoemaker introduce supply chain vigilance, a system which brings a wide-angle view and disciplined scrutiny to scanning and managing the supply chain’s broader ecosystem.
This study redefines information power and informational justice as information competencies drawing upon information-related theories. Furthermore, it investigates their impact on information sharing and logistics performance within inter-firm relationships in the supply chain context. To analyze their correlations and causal relationships, a survey was conducted with employees working in departments associated with supply chain management (SCM) in South Korea. A total of 300 copies of the questionnaire were used in statistical analysis, and a structural equation model was used for hypothesis testing. The findings indicate that both information power and informational justice exert a significant positive influence on information sharing. Moreover, information sharing significantly enhances logistics performance, serving as an outcome variable. This study integrates concepts related to information into a single framework called information competencies, while also redefining the role of information sharing. Inputs for academic scalability and practical implications for supply chain participants are discussed.
With the deepening of industrial division of labor, supply chain efficiency has become a critical driver of companies' core competitiveness. Using a sample of Chinese A‐share listed companies from 2007 to 2023, this paper empirically investigates the impact of digital transformation on supply chain efficiency. We find that firms with a higher degree of digital transformation are associated with higher supply chain efficiency. Mechanism tests show that digital transformation facilitates supply chain efficiency via lower customer demand uncertainty as well as raw material disruption risk. The positive effect of digital transformation is more pronounced for non‐state‐owned enterprises and for firms with less stable customers and more geographically dispersed suppliers. Moreover, there is much degree prompt in supply chain efficiency for firms located in a better digital environment. This paper sheds light on how digital transformation influences supply chain efficiency and provides significant insights for firms to improve supply chain efficiency.
This book investigates the growing influence of artificial intelligence in the marketing sphere, providing insights into how AI can be harnessed for developing more effective and efficient marketing strategies. In addition, the book will also offer a comprehensive overview of the various digital marketing tools available to entrepreneurs, discussing their features, benefits, and potential drawbacks. This will help entrepreneurs make well-informed decisions when selecting the tools most suited to their needs and objectives. It is designed to help entrepreneurs develop and implement successful strategies , leveraging the latest tools and technologies to achieve their business goals. As the digital landscape continues to evolve rapidly, this book aims to serve as a valuable resource for entrepreneurs looking to stay ahead of the curve and capitalize on new opportunities. The book's scope encompasses a wide range of topics, including customer experience, content marketing, AI strategy, and digital marketing tools.
This paper investigates a risk-averse firm's investment strategy in real-time event-monitoring technologies coupled with dynamic disruption response decisions. The firm does not know how long the disruption will last, and the event-monitoring solutions provide the firm with a quicker update regarding the length of the disruption. When the firm receives an update, it has the flexibility to revise its initial response action. We model a two-stage stochastic program to study this problem where risk aversion is modeled in the form of a Service-at-Risk constraint. Our paper makes four important contributions. First, it characterizes the optimal recourse strategies given an update and identifies the conditions when the firm benefits from the recourse. Second, we characterize the optimal investment and initial response strategies where we find that the investment behavior is non-monotone. Third, our paper shows an interesting impact of risk aversion on the investment decision such that the firm may benefit from investing in event monitoring at moderate degrees of risk aversion, but not necessarily at low or high degrees of risk aversion. Fourth, we find that a firm's benefit from event monitoring is more profound when the capacity of contingency response is moderately limited.
This chapter overviews the challenges in pharmaceutical supply chains (PSCs) in Low- and Middle-Income Countries (LMICs), with a focus on Sierra Leone. Furthermore, it describes how traditional supply chain optimization strategies can be used to improve performance of PSCs in Sierra Leone. Finally, it describes the significant potential for using machine learning in this framework for effective demand forecasting. We highlight challenges such as limited data availability, the need to ensure equitable distribution, as well as the potential for transfer learning to address some of these challenges.
This paper presents a unifying model of disclosure in the presence of competitors and supply market reliance to examine the role of multisegment operations on disclosure choice. A firm’s private information can have varying demand implications for its own portfolio of segments and for its competitors’ portfolios of segments. In multisegment firms, cross-firm spillovers of information discourage disclosure whereas cross-segment spillovers encourage disclosure. This suggests multisegment firms with more informationally diverse segments will have more incentives for transparency. Further, in multisegment firms, reliance on an imperfect supply market has less detrimental effects on transparency compared to single-segment firms. Supply market reliance is less detrimental for multisegment firms with a more diverse portfolio of segments. The results suggest that multisegment firms have more incentives for transparency relative to single-segment firms.
JEL Classifications: L11; L13; M41.
Purpose
This study aims to introduce a multilevel micro-foundational perspective on supply chain (SC) ambidexterity, grounded in organizational learning and adaptation research. It investigates the interplay of contextual factors, strategic orientation and a bundle of supply chain management practices to foster ambidextrous performance.
Design/methodology/approach
Leveraging a blend of perceptual and objective data and measures, this study explores the intricacies of macro and micro factors at multiple levels, offering empirical support for the research framework. The interrelationships among these factors are scrutinized through three analytical approaches: selection, interaction and system forms of interdependence analysis.
Findings
First, the authors offer empirical support for their conceptual model, illustrating that ambidexterity behavior and outcomes in the SC emanate from intricate interactions between macro and micro factors across various levels. Second, the authors present robust empirical evidence endorsing a system/gestalt form of interdependence analysis in capturing SC ambidexterity and performance. This analytical approach effectively captures the complementarity and contradictory interdependence among the opposing poles of efficiency and responsiveness.
Originality/value
The organizational and SC activity configuration faces numerous paradoxical tensions, such as profitability versus sustainability. This study offers valuable insights into establishing an ambidextrous system capable of navigating and addressing these paradoxical situations.
Firmalar için yer aldıkları tedarik zincirlerini geliştirmek ve daha etkili kılmak, küresel rekabet ortamında hayatta kalmak adına önemlidir. İş birlikçi Planlama, Tahmin ve İkmal (İPTİ) tedarik zinciri katılımcıları arasında iş birliğini teşvik eden ve taraflar arasında ortak fayda sağlamayı amaçlayan bir süreç yönetim stratejisidir. İPTİ ile üreticiler ile tedarikçileri ve müşterileri arasında etkin iş birlikleri mümkündür. Bir firmanın tedarik zincirinde çok sayıda müşteri ve tedarikçi yer alıyorsa her bir iş birliği için ayrı çaba sarf etmek yerine bir iş analitiği yöntemi olan ikili kümeleme kullanılarak iş birliği kurma süreci daha hızlı ve daha düşük maliyetle gerçekleştirilebilir. İkili kümeleme, çok sayıda iş birliği kurma ihtiyacını tedarik zincirindeki müşterilerin ortak özelliklerine göre gruplandırarak azaltabilir. Bu nedenle, ikili kümeleme ve İPTİ, tedarik zincirinde verimliliğini artırmak için beraber kullanılabilecek değerli araçlardır. Bu tekniklerin birleştirilmesi, rekabet avantajının artırılmasına ve tedarik zinciri operasyonlarının daha başarılı bir şekilde yönetilmesine yardımcı olabilir. Bu çalışmada otomotiv yan sanayi sektöründe faaliyet gösteren bir firma, ikili kümeleme stratejisini kullanarak birden fazla müşteriyle tek bir iş birliği gerçekleştirmiştir. Bulgular, firmanın birden fazla müşterisiyle beraber çalışmasına olanak tanıyan ikili kümelemenin potansiyel faydalarını ortaya koymuştur. Bu stratejinin işletmelere müşteri odaklı girişimler oluşturma, envanter kontrolünü kolaylaştırma ve tedarik zinciri etkinliğini artırma gibi faydalar sağlayabileceği açıktır.
The push for more battery-powered electric vehicles (BEV), the COVID-19 pandemic, and other global supply chain destabilizing events (e.g., the war in Ukraine), have made it necessary for manufacturers to consider innovative approaches to sourcing and materials management. This study assesses the value of sharing delivery due date updates, which are then used to convert spent time into a fraction of the expected total time for order fulfillment (i.e., progress updates), to synchronize the delivery of components for an automotive manufacturer who, amid long and variable lead times for semiconductor chips, maintains a strategy of waiting for the delivery of all needed parts before commencing production. Having progress updates in a fractional form puts numerical bounds (i.e., 0 to 100%) on the shared information, and this facilitates closed-form analytical comparisons. We develop analytical models to show decreases in expected assembly-related costs based on the progress update information shared between two suppliers— one supplier has a shorter and more reliable order fulfillment lead time than the other. When there are more than two suppliers, we use a simulation model to estimate the expected value of sharing progress updates. Our results show that increasing the frequency of shared progress updates, and having more suppliers share progress updates, results in increased cost-savings percentages. However, the opposite occurs with increasing uncertainty in suppliers’ delivery lead times. The computational study provides support for the existence of a critical mass level of suppliers needed to achieve a given percentage cost saving. This study can help automakers to make informed decisions on encouraging information sharing among suppliers, by first creating a critical mass of suppliers to share progress updates. Our investigations also help show the conditions in which to best leverage such information sharing strategies while waiting for the delivery of all needed components prior to production.
In this paper, we consider an adaptive base-stock policy for a single-item inventory system, where the demand process is nonstationary. In particular, the demand process is an integrated moving average process of order (0, 1, 1), for which an exponential-weighted moving average provides the optimal forecast. For the assumed control policy we characterize the inventory random variable and use this to find the safety stock requirements for the system. From this characterization, we see that the required inventory, both in absolute terms and as it depends on the replenishment lead-time, behaves much differently for this case of nonstationary demand compared with stationary demand. We then show how the single-item model extends to a multi-stage, or supply-chain context; in particular we see that the demand process for the upstream stage is not only nonstationary but also more variable than that for the downstream stage. We also show that for this model there is no value from letting the upstream stages see the exogenous demand. The paper concludes with some observations about the practical implications of this work.
(This article originally appeared in Management Science, April 1997, Volume 43, Number 4, pp. 546--558, published by The Institute of Management Sciences.) Consider a series of companies in a supply chain, each of whom orders from its immediate upstream member. In this setting, inbound orders from a downstream member serve as a valuable informational input to upstream production and inventory decisions. This paper claims that the information transferred in the form of ÜordersÝ tends to be distorted and can misguide upstream members in their inventory and production decisions. In particular, the variance of orders may be larger than that of sales, and distortion tends to increase as one moves upstreamÔa phenomenon termed Übullwhip effect.Ý This paper analyzes four sources of the bullwhip effect: demand signal processing, rationing game, order batching, and price variations. Actions that can be taken to mitigate the detrimental impact of this distortion are also discussed.
Many companies have embarked on initiatives that enable more demand information sharing between retailers and their upstream suppliers. While the literature on such initiatives in the business press is proliferating, it is not clear how one can quantify the benefits of these initiatives and how one can identify the drivers of the magnitudes of these benefits. Using analytical models, this paper aims at addressing these questions for a simple two-level supply chain with nonstationary end demands. Our analysis suggests that the value of demand information sharing can be quite high, especially when demands are significantly correlated over time.
This paper develops a new model for studying multiechelon inventory systems with stochastic demand. For the model we assume that each site in the system orders at preset times according to an order-up-to policy, that delivery times are deterministic, and that the demand processes are stochastic with independent increments. We introduce a new scheme for allocating stock in short supply, which we call virtual allocation and which permits significant tractability. We exercise the model on a set of test problems for two-echelon systems to get insight into the structure of good policies. The primary findings are that both the central warehouse (upper echelon) and the retail sites (lower echelon) should hold safety stock, but that most of the safety stock should be at the retail sites. Consequently, the central warehouse will stock out with high probability. Furthermore, we show that the virtual allocation rule is near optimal for the set of test problems.
In the last several years there have been a number of papers discussing optimal policies for the inventory problem. Almost without exception these papers are devoted to the determination of optimal purchasing quantities at a single installation faced with some pattern of demand. It has been customary to make the assumption that when the installation in question requests a shipment of stock, this shipment will be delivered in a fixed or perhaps random length of time, but at any rate with a time lag which is independent of the size of the order placed. There are, however, a number of situations met in practice in which this assumption is not a tenable one. An important example arises when there are several installations, say 1, 2, ..., N, with installation 1 receiving stock from 2, with 2 receiving stock from 3, etc. In this example, if an order is placed by installation 1 for stock from installation 2, the length of time for delivery of this stock is determined not only by the natural lead time between these two sites, but also by the availability of stock at the second installation. In this paper we shall consider the problem of determining optimal purchasing quantities in a multi-installation model of this type.
We incorporate information flow between a supplier and a customer in a two-echelon model that captures the capacitated setting of a typical supply chain. We consider three situations: (1) a traditional model where there is no information to the supplier prior to a demand to him except from past data; (2) the supplier has the information of the (s,S) policy used by the customer as well as the end-product demand distribution; and (3) the supplier has full information about the state of the customer. We show that order up-to policies continue to be optimal for models with information flow for the finite horizon, the infinite horizon discounted and the infinite horizon average cost cases. We develop solution procedures to compute the optimal parameters. Study of these three models enables us to understand the relationships between capacity, inventory and information at the supplier level and how they are affected by customer S Gamma s values and end-item demand distribution. We...
A two-echelon distribution inventory system is studied with a central warehouse and N retailers. A method is presented for exact evaluation of control policies that provides the complete probability distributions of the retailer inventory levels. All important consequences of different continuous review installation stock (R,Q) policies are analyzed.
We consider a serial inventory system with N stages. The material flows from an outside supplier to stage N, then to stage N - 1, etc., and finally to stage 1 where random customer demand arises. Each stage replenishes a stage-specific inventory position according to a stage-specific reorder point/order quantity policy. Two variations of this policy are considered. One is based on echelon stock, and the other installation stock. The former requires centralized demand information, while the latter does not. The relative cost difference between the two policies is called the value of centralized demand information. For fixed order quantities, we develop efficient algorithms for computing both the optimal echelon reorder points and the optimal installation reorder points. These algorithms enable us to conduct an extensive computational study to assess the value of centralized demand information and to understand how this value depends on several key system parameters, i.e., the number of stages, lead times, batch sizes, demand variability, and the desired level of customer service.
We consider a two-level inventory system with one warehouse and N identical retailers. Lead times (transportation times) are constant and the retailers face independent Poisson demand. In a previous paper [ibid. 38, No. 1, 64-69 (1990; Zbl 0715.90039)], we derived a recursive procedure for determining the policy costs for an average item in case of one-for-one replenishment policies. In this paper, we show how these results can be used for the exact or approximate evaluation of more general policies where both the retailers and the warehouse order in batches. We compare our methods to the method recently suggested by A. Svoronos and P. Zipkin [‘Evaluation and optimization of one- for-one replenishment policies for multiechelon inventory systems’, Grad. School of Business, Columbia University, New York (1986)].
B. Deuermeyer and L. B. Schwarz [in: Multilevel production/inventory control systems: theory and practice, TIMS Stud. Manage. Sci. 16, 163-193 (1981; Zbl 0469.90031)] have developed a very simple approximation of a complex multi-echelon system. Here we propose several refinements of their techniques, leading to models nearly as simple and considerably more robust. Our analysis suggests guidelines for the design of large-scale logistics systems, differing markedly from those of earlier studies. An algorithm is developed for calculating the probabilities of the number of busy devices in two and three sequential completely accessible groups (of devices) in the case of servicing of the flow with losses and a simple after-effect. Expressions are found for determining the throughput of the first, last, and any intermediate device of a completely accessible group in the case of ordered occupation (of devices). It is shown that the throughput of the last device differs from the increment in the throughput of the system resulting from the addition of one device to the system.
We consider a one-warehouse,N-identical-retailer model. Random demands occur at the retailers with complete backlogging. The retailers replenish their inventories from the warehouse, which in turn orders from an outside supplier with unlimited stock. Each retailer places an order everyN periods according to a base-stock policy, and the reorder intervals of the retailers are staggered so that only one retailer places an order in each period. The warehouse orders according to an ( s, S) policy based on its own inventory position. We consider two allocation policies, past priority allocation (PPA) and current priority allocation (CPA), which specify how the retailer orders are filled at the warehouse. For the PPA model, we provide an exact procedure for computing the long-run average total cost. Based on the exact procedure, we develop an approximate model that can be used to determine near-optimal control parameters for both the PPA and the CPA model. We conduct a computational study to test the effectiveness of the approximate model and to compare the performance of the two allocation policies.
We consider a distribution system with a central warehouse and multiple retailers. The warehouse orders from an outside supplier and replenishes the retailers which in turn satisfy customer demand. The retailers are nonidentical, and their demand processes are independent compound Poisson. There are economies of scale in inventory replenishment, which is controlled by an echelon-stock, batch-transfer policy. For the special case with simple Poisson demand, we develop an exact method for computing the long-run average holding and backorder costs of the system. Based on this exact method, we provide approximations for compound Poisson demand. Numerical examples are used to illustrate the accuracy of the approximations. We also present a numerical comparison between the average costs of a heuristic, echelon-stock policy and an existing lower bound on the average costs of all feasible policies.
This paper discusses the relationship between business process reengineering and channel performance for firms implementing electronic data interchange (EDI) linkages within the U.S. grocery industry. Both quantitative and qualitative data sources are combined to test the hypothesis that channel transformation involving adoption of EDI and redesign of replenishment processes enables performance improvements more than an order of magnitude greater than implementation of EDI alone. This new process, enabled by EDI, provides retailers with 50- 100% higher inventory turns for products on continuous replenishment processes (CRP) relative to retailer performance using traditional ordering processes. Firms adopting EDI without using CRP to reengineer the ordering processes have failed to realize any statistically significant improvements in either inventory levels or warehouse stockouts. This research provides evidence to support the claims of process reengineering that are common in the popular business press, but for which statistically significant empirical evidence is minimal. The findings of the research also demonstrate the potential improvements that firms can realize through extending the business process reengineering concept to include the firms' entire supply chain.
Campbell Soup's continuous replenishment (CR) program is a novel innovation designed to improve the efficiency of inventory management throughout the supply chain. With CR (1) retailers pay a constant wholesale price but continue to participate in consumer promotions, (2) retailers transmit to the supplier daily inventory information via electronic data interchange (EDI), and (3) the supplier assumes responsibility for managing retailer inventories, i.e., vendor managed inventories (VMI). We develop simple inventory management rules to operate CR, and we test these rules with a simulation using actual demand data provided by Campbell Soup. On this sample we find that retailer inventories were reduced on average by 66% while maintaining or increasing average fill rates. This improvementreduces a retailer's cost of goods sold by 1.2%, which is significant in the low profitmargin grocery industry. Furthermore, these savings could have been achieved without VMI.
We model the effects of alternative coordination structures on the performance of a firm that faces uncertain demand in multiple horizontal markets. The firm's coordination structure is jointly determined by its decision-rights structure and by its information structure. We compare the performance of decentralized, centralized and distributed structures and study factors that affect the value of coordination. The results quantify and illustrate the value of co-locating decision rights with specific knowledge.
We establish lower bounds on the minimum cost of managing certain production-distribution networks with setup costs at all stages and stochastic demands. These networks include serial, assembly, and one-warehouse multi-retailer systems. We obtain the bounds through novel cost-allocation schemes. We evaluate the bounds' performance for one-warehouse multi-retailer systems by comparing them with simple, heuristic policies. The bounds are quite tight for systems with a small number of retailers. We also present simplified proof of known optimality results for serial and assembly systems.
For a system of N-identical-retailers we construct a model for determining warehouse inventory-allocation policies which minimize system lost sales per retailer between system replenishments. An allocation policy is specified by: (a) the number of withdrawals from warehouse stock; (b) the intervals between successive withdrawals; (c) the quantity of stock to be withdrawn from the warehouse in each interval; and (d) the division of withdrawn stock among the retailers. We show that in the case of two withdrawals, available stock in each interval should be divided to “balance” retailer inventories.
We also develop an infinite-retailer model and use it to determine two-interval allocation heuristics for N-retailer systems. Simulation tests suggest that the infinite-retailer heuristic policies are near-optimal for as few as two retailers. Simulation tests indicate that the risk-pooling benefits of allocation policies with two well-chosen intervals are comparable to those of base-stock policies with four equal intervals.
In multi-echelon repairable inventory systems with high set-up cost for order and/or high demand rates, the use of batch ordering may be more cost-effective than the common (S - 1, S) ordering policy. This paper addresses the issue of determining the optimal order batch size and stocking levels at the stocking locations in such a system. A power approximation is used to estimate the total system stock and backorder levels from which the optimal batch size can be readily determined. A search routine involving "one-pass" searches are then followed to obtain the stocking levels at the depot and the local sites of the system. This procedure has been evaluated using 900 test cases and has been found to be very effective. The power approximation approach also results in a simple analytical relationship to test whether or not (S - 1, S) is an optimal ordering policy for repairable items in a multi-echelon environment.
Electronic Data Interchange (EDI) and related technologies are making it less expensive to frequently transmit demand information up the supply chain from the point of sale. However, little is known about how the various participants in the supply chain might exploit more timely demand information. This research is intended to be an opening contribution to the analytical study of timely demand information. We study a simple two-level system composed of a supplier (or component plant) and a single customer (or final assembly plant). The two factories use a standard periodic base-stock policy for one particular item, but the equal-length production cycles of the two factories do not necessarily coincide. Both participants hold inventories to buffer the effects of uncertain orders and uncertain deliveries. The supplier is in turn supplied by a source with infinite capacity. Final demand occurs only at the final assembly plant, which communicates demand over its order cycle to the component plant. If the component plant begins a production cycle between orders from the final assembly plant, it is uninformed about some number of days' demand which has been observed at the customer but not yet communicated. Any technology, such as EDI, that makes it cheaper for the customer to communicate demand as it occurs allows the supplier to base its decisions on more accurate information. With more accurate demand information the supplier could reduce inventories, or improve the reliability of its deliveries to its customer, or both. The customer, in turn, could reduce its inventories if its supplier were more reliable. We examine the changes brought about by the exchange of timely demand information in inventories and service levels at both the supplier and customer. Our results show that inventory-related benefits are particularly sensitive to demand variability, the service level provided by the supplier, and the degree to which the order and production cycles are out of phase.
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