Journal of Modelling in Management

Published by Emerald
Online ISSN: 1746-5664
Publications
Article
Purpose – The purpose of this article is to identify the critical success factors (CSFs) of knowledge management (KM) adoption in the supply chain (SC) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method through an empirical case study. Design/methodology/approach – The paper examines the influencing factors of KM adoption in SC which have been identified through the literature survey and expert opinion. The fuzzy DEMATEL method has been used to evaluate identified influencing factors. Considering the interdependence among factors, the fuzzy DEMATEL method forms a structural model and then visualizes the causal relationships among factors through a cause–effect relationship diagram. On the basis of the cause–effect relationship diagram, CSFs that are extraordinarily essential for KM adoption in SC are identified. Empirical case study of an Indian automobile organization presented to illustrate the fuzzy DEMATEL method and demonstrates its usefulness. Findings – The results gathered from the implementation of the fuzzy DEMATEL method to identify CSFs of KM adoption in SC to the chosen case illustrate that factors such as top management support, employee training and education, integration of knowledge and information flow, communication among the SC members and trustworthy teamwork to exchange knowledge within SC need to be highlighted as critical factors for successful adoption of KM in SC. Practical implications – The finding not only offers a meaningful base to deepen the understanding with regard to KM adoption in SC, but also provides a clue to develop an effective adoption of KM in SC in a stepwise manner. Originality/value – The empirical case study contributes to the literature on KM adoption in SC, suggesting how an organization can identify CSFs of KM adoption in SC and implement them progressively to greatly improve the efficiency of the whole SC performance.
 
Article
Purpose – This paper aims at developing an interpretive structural model of drivers for environmentally conscious manufacturing (ECM). It will demonstrate how interpretive structural modeling (ISM) supports policy makers in the government and industry in identifying and understanding interdependencies among drivers for ECM. Interdependencies among drivers will be derived and structured into a hierarchy to derive subsystems of interdependent elements with corresponding driving power and dependency. Design/methodology/approach – ISM has been used to identify hierarchy and inter-relationships among drivers for ECM adoption and to classify the drivers according to their driving and dependence power using MICMAC analysis. The drivers for ECM adoption are identified through the review of literature followed by developing a model of drivers using ISM. Findings – The main findings of the paper include the development of an ISM model of drivers for ECM adoption. The developed model divided the identified drivers into five levels of hierarchies showing their inter-relationship and depicting the driving-dependence relationship. These five levels have been classified into four categories – awareness, external, organizational and benefits. Originality/value – The developed ISM model is expected to provide a direction to the policy makers in the government and industry and the top management of the organizations to leverage their resources in a timely manner to adopt ECM successfully.
 
Graph showing categories of SCA enablers  
Article
Purpose – The purpose of this paper is to present an approach to effective supply chain management by understanding the dynamics between various enablers of agile supply chain. Today’s business environment is characterized as a highly competitive, dynamic and volatile market. Agile supply chain is seen as the winning strategy to be adopted by manufacturers bracing themselves for dramatic performance enhancements to become national and international leaders. Design/methodology/approach – Using interpretive structural modeling the research presents a hierarchy-based model and the mutual relationships among the enablers of agile supply chain. Findings – The research shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance, whereas another group consists of those variables which have high dependence and are the resultant actions. Practical implications – This classification provides a useful tool to supply chain managers to differentiate between independent and dependent variables and their mutual relationships which would help them to focus on those key variables that are most important for building cost-effective and agile supply chains. Originality/value – Presentation of enablers in a hierarchy and the classification into driver and dependent categories is unique effort in the area of agile supply chain management.
 
Article
Purpose – The purpose of this paper is to implement a multi-criteria preference disaggregation approach to measure logistics service quality (LSQ) of manufacturing companies’ supply chains. Design/methodology/approach – A total 216 Greek manufacturing companies took part in a survey with the use of a dedicated questionnaire. They were asked to assess the LSQ of their primary supplier regarding a predefined set of criteria and sub-criteria. The data were analysed with the multi-criteria satisfaction analysis method, which represents an ordinal regression based approach used for customer satisfaction measurement. Findings – Weak points of the suppliers as well as dimensions that drive satisfaction were identified. Furthermore, the competitive advantages of the suppliers as well as their priorities for improvement were spotted. Research limitations/implications – The sampling framework, including only the manufacturing companies operating in a specific area of Greece, does not ensure the full generalisation of the results. A larger sample of manufacturing companies from all over Greece would be useful to obtain more reliable results and would enable the comparison of LSQ for different manufacturing sectors. Practical implications – The method used to assess LSQ of manufacturing companies can be installed as a permanent customer satisfaction barometer to measure, control and improve the LSQ provided to manufacturing companies as well as to other business sectors. Originality/value – This paper proposes a method to explore the relationships between LSQ and industrial customers’ satisfaction to prioritise strategic plans of companies in the supply chains.
 
Article
Purpose – The purpose of this study was to explore the impact of the formation of industrial clusters on the obtainment of professional human resources, to verify the impact of human resources on clustering relationships and firm’s performance and to understand whether the formation of clusters can contribute to the obtainment of professional human resources and the improvement of competitiveness of enterprises. It was expected that solutions could be found to make new contributions through the verification of special economic zones (SEZs). Design/methodology/approach – Using manufacturers in Taiwan’s SEZs as the subjects, this study explored the impact on the obtainment of professional human resources after the formation of industrial clusters in SEZs, through conducting and empirical study with a questionnaire survey. Findings – The professional human resources are the essential factor for the formation of industrial clusters and the improvement of competitiveness. This study also confirmed that industries can have professional human resources by industrial clustering and that this will produce a positive impact on the enterprise clustering relationships, which can also have a positive impact on firm’s performance and can enhance the enterprise’s competitive advantage. Practical implications – Industrial clustering is the key factor to attract professional human resources; industrial clusters can enhance firm’s performance; and professional human resources affect firm’s performance of enterprises. Originality/value – No study has discussed the topic of clusters from the perspective of SEZs also including six export processing zone (EPZ) parks in Taiwan. This study discussed the topic using theories relating to clustering and human resources. The formation of industrial clusters can result in higher competitiveness in the face of the global market. The EPZ industrial cluster provides an excellent investment environment. Coupled with one-stop express services and geographic advantage, the land-use rate is up to 97 per cent and the per hectare output value amounts to NTD 3.2 billion, setting a successful example of an industrial cluster.
 
Comparison of fits of the group learning curve and two alternative learning curves for empirical data 
Impact of ci,j, sj,i and ri,j on the transfer of knowledge in the group 
Article
Purpose – The purpose of the paper is to develop a mathematical model that describes group learning processes with and without worker turnover. Design/methodology/approach – Based on an extensive literature review, fundamental characteristics of group learning processes are first identified and then incorporated into a group learning curve (GLC). The developed GLC is then validated by fitting to empirical data. Findings – The results show that the behaviour of the developed model is in conformance with the characteristics identified in the literature. A comparison with two other learning curves that have frequently been discussed in the literature shows that the GLC developed in this paper is a good mathematical representation of group learning processes. Practical implications – The model developed in this paper enables practitioners to predict performance improvement in groups. Originality/value – The paper is one of the first to propose a mathematical formulation of a GLC.
 
Article
Since Shalit and Yitzhalit (1984) the Mean-Extended Gini (MEG) has been proposed as a workable alternative to the classical Markowitz mean-variance CAPM. Although MEG keeps under control the risk belonging to the left-tail of the return distribution, small attention is reserved to potential gains belonging to the return right-tail. A generalization of MEG able to select personalized optimal mean-risk and/or mean-gain portfolios is proposed. We give evidence that if the portfolio distributions are symmetrical and/or the investor has a moderate risk-gain profile, then the efficient mean-risk portfolio always coincides with the worst inefficient mean-gain portfolio. Vice versa, if we concern more realistic scenarios admitting the existence of asymmetrically distributed assets and/or investors with very defensive or very aggressive investment profiles, portfolios which are optimal under both criteria may exist.
 
Article
Purpose – The impact of transportation on the supplier selection has received very scant attention in the literature. This is a great limitation because splitting orders across multiple suppliers will lead to smaller transportation quantities which will likely imply larger transportation cost. Moreover, transportation and inventory elements are highly interrelated and contribute most to the total logistics costs. This paper seeks to present a nonlinear multiobjective programming approach of selecting suppliers and allocating the order quantity among them, taking into account transportation. Design/methodology/approach – The model considers the total product cost and the lead‐time as the criteria to minimize simultaneously. Findings – The total cost is the sum of transportation, inventory and ordering costs. The constraints related to suppliers and buyer are also considered in the model. The model is solved several times, evaluating various scenarios. Each scenario depends on the shipment type used between the suppliers and the buyer. Originality/value – This paper fills a gap in the literature by comprehensively examining the role of transportation in determining the optimal number of suppliers and the portion of the order to allocate to each one.
 
Article
Purpose The purpose of this paper is to provide an insight into the use of an integrated approach of fuzzy analytical hierarchy process (fuzzy AHP) and TOPSIS in evaluating the performance of global third party logistics service providers for effective supply chain management. Design/methodology/approach In this study, the integration of fuzzy AHP with TOPSIS is proposed in determining the relative importance (weight) of criteria and then ranking of 3PLs. Findings Findings show that the logistics cost and service quality are two most important criteria for performance rating of 3PLs. Deciding the relative importance of various criteria for 3PLs evaluation is a complex task. The superiority of one criterion over the other varies from person to person and firm to firm. Therefore, to capture the variability in decision fuzzy extended AHP is very useful tool. Finally, the preference raking of alternatives are found using TOPSIS. Research limitations/implications Fuzzy AHP is a complex methodology and requires more numerical calculations than the traditional AHP and hence it increases the effort. But in this paper single stage fuzzy AHP is used to simplify the process. Fuzzy AHP is integrated with TOPSIS for preference ranking of 3PL, which provides a good methodology to rank 3PLs. Originality/value There is a lack of research in the literature to deal directly with the uncertainty of human decisions in evaluating the relative importance of multiple criteria. Therefore, fuzzy AHP is an appropriate methodology to find the relative importance of the criteria to rank the 3PLs using TOPSIS.
 
Article
Purpose ‐ The aim of this research is to provide an approach for modeling system risk management and to develop an analytic hierarchy process (AHP)-based model for simulating decisions on introducing innovations in air transport systems. Design/methodology/approach ‐ The paper proposes AHP and analytic network process (ANP) methodologies for overcoming fragmentation in risk assessments perceived by risk, budget, quality or schedule managements, and for resolving potential conflicts between safety, efficiency and well-being. Findings ‐ Issues in system risk evaluation and management were identified and transferred to a list of requirements. A generic ANP-based model for system risk management was developed as well as a template for capture of knowledge on risks, including expert knowledge, and for implementation of a new decision-making process as applied to introducing innovation(s). Research limitations/implications ‐ Since this research addresses evaluation and management of non-event based risks due to innovations in air transport systems, further analysis and re-evaluation of risks is required during and after the implementation in order to provide continuously dynamic representation of system risk. Practical implications ‐ The results of this study contribute to the development and implementation of a usable version of multi-criteria decision analysis at senior management level. Further, it stimulates mechanism for learning and trade-offs between various stakeholders. Originality/value ‐ This work is original in that it is cross-disciplinary (e.g. risk management, management of innovation, systems design). It addresses the issue of integrating a safety management system with an overall business management system. Also, it introduces qualitative non-event risk assessments into system risk management. In addition to the use of the AHP-model for system risk management, an implementation model ("risk stakeholder model") is also developed.
 
Article
Purpose – The paper aims at the bi‐objective optimization of a two‐echelon distribution network model for facility location and capacity allocation where in a set of customer locations with demands and a set of candidate facility locations will be known in advance. The problem is to find the locations of the facilities and the shipment pattern between the facilities and the distribution centers (DCs) to minimize the combined facility location and shipment costs subject to a requirement that maximum customer demands be met. Design/methodology/approach – To optimize the two objectives simultaneously, the location and distribution two‐echelon network model is mathematically represented in this paper considering the associated constraints, capacity, production and shipment costs and solved using hybrid multi‐objective particle swarm optimization (MOPSO) algorithm. Findings – This paper shows that the heuristic based hybrid MOPSO algorithm can be used as an optimizer for characterizing the Pareto optimal front by computing well‐distributed non‐dominated solutions. These aolutions represent trade‐off solutions out of which an appropriate solution can be chosen according to industrial requirement. Originality/value – Very few applications of hybrid MOPSO are mentioned in literature in the area of supply chain management. This paper addresses one of such applications.
 
Article
Purpose ‐ This conceptual paper aims to shed light on the nature and determinants of managerial behaviour when affected by supply chain disruptions. It aims to argue that the managerial decision-making process is an important component in determining the eventual long-term impact of a supply chain disruption. Design/methodology/approach ‐ The paper introduces a continuous simulation model that is based on a Bayesian robot decision-maker. Using the system dynamics approach, it illustrates the process of evaluating competing hypotheses of functional vs dysfunctional supply chain design in a disruption scenario. Model validity is assessed by means of a case study based on secondary data. Findings ‐ The model provides insight into the drivers of decision-maker confidence dynamics that are used when evaluating the competing hypotheses. Furthermore, it identifies the psychological distortions that make actual managerial inference processes different from the Bayesian robot and incorporate these adjustments into the system dynamics model. Several propositions about the nature and determinants of decision-maker confidence are stated. Practical implications ‐ For policy makers, the paper clarifies the important moderating role of confidence in the realisation of wider implications of supply chain disruptions, especially from the perspective of industrial development, and trade and transport facilitation. Originality/value ‐ The research enhances understanding of the wider implications of supply chain disruptions, contributing to behavioural research in logistics and supply chain management.
 
Article
Purpose ‐ This research aims to provide guidance for management of green service supply chains to improve the likelihood and extent of innovation and joint productivity performance for value creation, with regard to coupling the potential role of the customer to increase supply chains performance. It is the purpose of this study to address the impact of green innovation privileged on service supply chains, then to address the prerequisite factors for enhancing the entire chain value creation. Design/methodology/approach ‐ A survey of extant research was undertaken for Egyptian hotels. It involved one type of questionnaire, provided across all managerial levels: top, senior, and executive managers. This questionnaire is divided into four main sections: the first section considers value creation, since the second section is related to trust; the third section is related to sharing knowledge; and the latest section is related to joint productivity. Findings ‐ The paper finds that it is possible to assist managers in thinking about adding value for supply chains. Research limitations/implications ‐ The study period interval in data collection may have influenced the variance in responses and therefore should be considered a limitation. Practical implications ‐ The ability to customize the simulator's parameters to represent value creation makes it a powerful tool for managers when deciding to rely on service supply chain. Originality/value ‐ This paper presents main elements required for enhancing value creation for all supply chain parties.
 
Article
Purpose ‐ The purpose of this paper is to develop a forecasting model for retailers based on customer segmentation, to improve performance of inventory. Design/methodology/approach ‐ The research makes an attempt to capture the knowledge of segmenting the customers based on various attributes as an input to the demand forecasting in a retail store. The paper suggests a data mining model which has been used for forecasting of demand. The proposed model has been applied for forecasting demands of eight SKUs for grocery items in a supermarket. Based on the proposed forecasting model, the inventory performance has been studied with simulation. Findings ‐ The proposed forecasting model with the inventory replenishment system results in the reduction of inventory level and increase in customer service level. Hence, the proposed model in the paper results in improved performance of inventory. Practical implications ‐ Retailers can make use of the proposed model for demand forecasting of various items to improve the inventory performance and profitability of operations. Originality/value ‐ With the advent of data mining systems which have given rise to the use of business intelligence in various domains, the current paper addresses one of the most pressing issues in retail management, as demand forecasting with minimum error is the key to success in inventory and supply chain management. The proposed forecasting model with the inventory replenishment system results in the reduction of inventory level and increase in customer service level. The proposed model outperforms other widely used existing models.
 
Article
Purpose – Contracting is an important issue in supply chain management. In this paper, the authors aim to discuss and compare the manufacturer's contracting options when the retailer faces a traditional newsvendor problem with a fixed retail price: a wholesale price only contract, a wholesale price discount contract, a returns policy contract, and a returns policy with the wholesale price discount contract. The paper also aims to examine how these contracting options affect decisions of the manufacturer and the retailer, as well as the supply chain efficiency. Design/methodology/approach – Models are developed based on the manufacturer's four contracting options. The manufacturer's optimal wholesale prices have been obtained. The ordering decisions of the retailer are discussed in each of the manufacturer's four contracting options. The paper also uses numerical examples to illustrate the author's managerial insights and results. Findings – As compared to the wholesale price only contract, it is found that implementing a wholesale price discount policy effectively encourages the retailer to order more product and enhances the retailer's profit at the expense of lowering the manufacturer's profit. It is also found that when the manufacturer offers a returns policy and if this policy cannot enhance the retailer's profit, a returns policy with the wholesale price discount contract can lead to a win‐win situation for both the manufacturer and the retailer. Originality/value – The research provides managerial insights on how different contracts affect decisions and efficiency of the supply chain.
 
Article
Purpose ‐ Nowadays, e-queues are built up everywhere where customer online service is necessary such as in banks' e-service, enterprises' e-business, etc. In order to enhance quality of service (QoS), active queue management (AQM) algorithms are frequently employed due to their efficiency in congestion avoidance as well as the differentiated forwarding of packets. This paper aims at developing a novel AQM algorithm to better QoS in terms of congestion prediction, queuing delay, packet loss and link utility, etc. Design/methodology/approach ‐ Upon the traditional designs of AQM, this paper establishes a new integrated AQM scheme (RQ-AQM) by employing input rate and current queue length to calculate the packet dropping/marking probability. In this way, the rate feedback control enables to rapid response to congestion, decreasing the packet loss from buffer overflow. Meanwhile, the queue length feedback control stabilizes the queue length around a given target, achieving predictable queuing delay and lower delay jitter. Thus, the main feature of the design is to use coefficients of both proportional rate control and proportional-integral queue length control, and to simplify parameter setting, the control parameters were scaled by the link capacity C to normalize the rate and by the bandwidth-delay product BDP to normalize the queue length, respectively. Findings ‐ The stability performance of RQ-AQM was tested via simulation under several conditions. The results proved that it is able to maintain the queue length around the given target. Also, the comparison results with other AQM schemes, including RED, ARED, PI controller, AVQ and REM, demonstrated the superiority of RQ-AQM in low packet loss, faster convergence to target queue length and closest to the target queue length. Research limitations/implications ‐ The main limitation of this study is that all the simulations were merely under a single bottleneck network topology. Furthermore, the system stability was examined under just a few cases. Other cases like TCP connections mixed with HTTP connections, or UDP flows, etc. can also be tested. Furthermore, the multiple bottleneck scenarios should be covered in the future work with more parameters set to enhance the proved results. Practical implications ‐ The paper sets clear but ideal conditions for the performance of proposed algorithm; so the simulation results can only be used as a rough reference instead of an exact practical one. But the concepts the paper attempted to advocate could be considered seriously. Social implications ‐ The scope of the paper is within the general theory of AQM. So it can be referred to any specific field that employs AQM technology, no matter locally or globally. Originality/value ‐ There are not much new brand contents in the paper. The main contribution is on some extension of the known related work.
 
Article
Purpose This study models the effects of the COVID-19 pandemic on the performance of the private health-care sector in the Middle East and North Africa (MENA) countries. This paper aims to address the economic, societal and sustainability of the health-care sector. Design/methodology/approach Data were collected from Bloomberg and the sample consists of 534 firm-year observations from 55 firms listed over 2010–2020. The authors apply panel data and control for the country and governance effects. Findings The authors found heterogeneous results regarding the three sub-sectors. The pandemic has a negative effect on the accounting and market performances of the “Pharmaceutical companies” and an insignificant impact on “Healthcare Management and Facilities Services.” Moreover, the impact of COVID-19 on health-care firms’ performance depends on the country’s economic classification and the degree of regulatory and governance frameworks. Research limitations/implications Further studies may consider a larger sample and other regions. It is recommended to address the health-care sector's challenges to invest in new technologies such as “digital twin” and predictive and personalized medicine. It is worth testing model development theory and its effects on speeding up and designing models to ensure the proper functioning and developing mathematics to determine uncertainties in patient data and model predictions. Originality/value To the best of the authors’ knowledge, this paper is novel as it is unique in modeling the impact of COVID-19 on the health-care public companies in the MENA region. The findings pinpoint firms’ and countries’ heterogeneous impacts on financial and market performances.
 
Article
Purpose Amid the COVID-19 contamination, people are bound to use contactless FinTech payment services. Because of restrictions on physical movement and avoidance of touching physical money, people willingly choose mobile payment, resulting in enormous growth in FinTech payment service industries. Because of this, this study aims to examine the effect of factors affecting Gen X and Millennials users to use FinTech payment services. Design/methodology/approach The authors used 328 responses collected through convenience sampling of Indian users aged between 26 and 57 years in the Delhi-NCR region who are users of FinTech payment services. Findings The authors’ findings verified that in India, perceived COVID-19 risk, perceived severity for COVID, individual mobility, subjective norms, perceived ease of use and perceived usefulness have statistically significant impacts on FinTech payment services during the COVID-19 pandemic. Structural equation modelling was used to study the proposed research model. Overall, the model predicted 76.9 % of the variation in intention to use FinTech payment services by the abovesaid variables by Indian users during a pandemic. Practical implications This study will provide valuable insight to all FinTech service providers and stakeholders in planning and designing the concerned policy. It will be able to draw the attention of users more. Originality/value This research added a valuable theory to the existing technology adoption model (TAM) theory. It demonstrated the utility of the above variables in adopting and using FinTech payment services, which will help service providers to develop future strategies because of the COVID-19 pandemic.
 
Article
Purpose This paper aims to assess the feasibility of a hybrid manufacturing and remanufacturing system (HMRS) for essential commodities in the context of COVID-19. Specifically, it emphasises using HMRS based on costs associated with various manufacturing activities. Design/methodology/approach The combination of mathematical model and system dynamics is used to model the HMRS system. The model was tried on sanitiser bottle manufacturing to generalise the result. Findings The remanufacturing cost is higher because of reverse logistics, inspection and holding costs. Ultimately remanufacturing costs turn out to be lesser than the original manufacturing the moment system attains stability. Practical implications The study put forth the reason to encourage remanufacturing towards sustainability through government incentives. Originality/value The study put forth the feasibility of the HMRS system for an essential commodity in the context of a covid pandemic. The research implemented system dynamics for modelling and validation.
 
Article
Purpose The purpose of this paper is to “identify”, “analyze” and “construct” a framework to quantify the relationships between several determinants of organizational preparedness for change in the start-ups during the COVID-19 emergencies. Design/methodology/approach Total interpretive structural modelling (TISM) is used to find characteristics that assist in analyzing the readiness or preparedness level before initiating a change deployment process in start-ups. A cross-impact matrix multiplication applied to classification (MICMAC) analysis is performed to determine the driving and dependent elements of change in start-ups. Findings From literature research and an expert interview, this study selected ten variables of change preparedness to explore inner interconnections and comprehend the inner connections factors. The findings depict that clarity of mission and goals, reward system, technological advancement and motivational readiness have been considered the most important readiness factor for deploying organizational change in start-ups during the COVID-19 emergencies. Practical implications This research will aid the management and researchers gain a better understanding of the factors that influence change preparedness. Constant observation of current changes in the start-ups and the external environment will aid in improving the quality of products or services provided by the start-ups during the COVID-19. The start-ups can use these criteria linked to change readiness. The priority of each element is determined using MICMAC analysis and ranking using the TISM technique, which assists start-ups in ordering the enablers from highest to lowest priority. Originality/value There is no research regarding factors influencing organizational readiness for change in start-ups during the COVID-19 emergencies. This research gap is filled by analyzing aspects linked to organizational readiness for change in start-ups. This gap inspired the present study, which uses the “Total Interpretive Structural Modelling (TISM)” technique to uncover change determinants and investigate hierarchical interconnections among factors influencing organizational readiness to change in start-ups during the COVID-19 emergencies.
 
Article
Purpose Presently, Indian sectors are manifesting a higher level of interdependency and making the economy more vulnerable to human-caused and natural disasters. COVID-19 pandemic creates a devastating effect on the world economy. The Indian economy was expected to lose around ₹ 32,000 crores every day during the first 21 days of complete lockdown. This motivates to conduct the research on how the COVID-19 pandemic affects the port logistics sector and how the effects of COVID-19 on port logistics propagate to other sectors owing to its interconnectedness and affect the economy of the country. Design/methodology/approach The purpose of the study is analyze how perturbation in one sector can affect the system of interdependent sectors and it is done with interdependency analysis. It uses Wassily Leontief’s inoperability input-output model (IIM) and interval programming (IP) to develop a framework. IP is used to address situations where assumptions are not valid because of uncertainties associated with disruptive events. Findings The model helps in describing how the effect of the COVID-19 pandemic in port logistics can propagate owing to the interconnectedness across other sectors. The model uses the latest five-year data available on the Organisation for Economic Co-operation and Development database. It uses metrics like inoperability and economic loss to study the consequences of COVID-19 pandemic on various sectors. This study also presents the ranking of the affected sectors based on their inoperability and economic loss Research limitations/implications In the future study, other techniques like dynamic evolution, multiplex network analysis, analytical hierarchy process, pinch analysis, stochastic evolution and pinch graph could be integrated with input-output (I-O) modelling. Integrated stochastic evolution with an I-O model allows capturing the likelihood of the events; it includes probability distributions instead of point estimates for scenario parameters. Methods like dynamic evolution and multiplex network analysis can be introduced in future work to shed lights on interdependency among the sector, which could potentially provide additional insights for transport policy formulations. Originality/value This study discusses the theory, methodology and application of the IIM-IP model in the domain of port logistics. The developed IIM-IP model helps decision-makers to manage risk in port logistics. Firstly, it studies how different sectors are interconnected with each other. Secondly, it helps in identifying the most vulnerable sectors based on economic loss and inoperability. Thirdly, it provides the ranking of the sectors based on their economic losses.
 
Article
Purpose The COVID-19 pandemic has impacted 222 countries across the globe, with millions of people losing their lives. The threat from the virus may be assessed from the fact that most countries across the world have been forced to order partial or complete shutdown of their economies for a period of time to contain the spread of the virus. The fallout of this action manifested in loss of livelihood, migration of the labor force and severe impact on mental health due to the long duration of confinement to homes or residences. Design/methodology/approach The current study identifies the focus areas of the research conducted on the COVID-19 pandemic. Abstracts of papers on the subject were collated from the SCOPUS database for the period December 2019 to June 2020. The collected sample data (after preprocessing) was analyzed using Topic Modeling with Latent Dirichlet Allocation. Findings Based on the research papers published within the mentioned timeframe, the study identifies the 10 most prominent topics that formed the area of interest for the COVID-19 pandemic research. Originality/value While similar studies exist, no other work has used topic modeling to comprehensively analyze the COVID-19 literature by considering diverse fields and domains.
 
Article
Purpose This paper aims to review and highlight the gaps in the research streams of the technological acceptance model (TAM) associated with e-banking services. The introduction of TAM as a decision-making process from individual and organizational perspectives is the core purpose of this paper. Design/methodology/approach This study is based on concept-centric reviews and synthesizing of previous research. Data are extracted from a systematic literature review published from 1975 to 2021 under the preferred reporting items for systematic review and meta-analyses statement. Findings This review explored that theory of reasoned action and theory of planned behavior are the basic theories proceeding to TAM evolution. TAM has been extended to its three versions, which are designed and modified for different contexts and cultures. Previously, the risk-return approach, theory of trust and perceived value were the major constructs or modifications in TAM. Now, TAM has been designed for measuring customers’ perception of any technological advancement. Research limitations/implications This review is limited to major additive constructs in modified TAM concerning e-banking services, which can be expanded to different cultures and contexts. This study sketched TAM as a decision-making model associated with the factors influencing any technological advancement. So, the proposed conceptual framework is applicable for the behavioral analysis of technological adoption from individual and organizational perspectives in any field. Originality/value This review designed a bi-dimensional conceptual model of TAM as a decision-making process for e-services that has not been identified yet in any study from organizations’ and customers’ perspectives.
 
Article
Purpose – This paper aims to present a literature review on models developed for the economic order quantity (EOQ) problem with incremental and all-units discounts, extending the work of Benton and Park (1996) which covered the most significant literature, from 1963 to 1994, about EOQ with discounts and that has identified four open areas in this field of study. The modeling of lot size with discounts wishes to give good solutions for realistic situations, such as those concerning the discounts offered by suppliers, to rises in the demand. Design/methodology/approach – The research was carried out in papers published from 1995 to 2013, and indexed in databases as Scopus and ISI Web of Science. The papers were compared through objective function, constraints, discounts, developed algorithms, allowance of shortages or multiproduct, demand pattern and buyer or buyer–supplier perspective. Findings – Results indicate two areas that still remain untouched, and probably the main cause is due to mathematical complexities. The authors have also identified an increasing trend of works that compared just-in-time with the EOQ with quantity discounts policy and also an increasing number of works that solved this category of problems with algorithms. Research limitations/implications – The research does not cover materials published in working papers, monographs, thesis, conferences or journals that are not indexed in those databases. Originality/value – This manuscript fills a gap in the study of EOQ with incremental discounts, as it highlights the leading edge advances in this field and the main differences among models. As a whole, the new trends about modeling EOQ problems with quantity discounts were discovered.
 
Article
Purpose Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances. Design/methodology/approach With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share. Findings The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity. Originality/value Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.
 
Article
Purpose The purpose of this paper is to propose a framework for evaluating and selecting the most optimal third-party logistics (3PL) service provider vendor among the available ones. Selection is done based on the performance values of the vendors on certain predefined criteria. Design/methodology/approach An integrated approach involving data envelopment analysis (DEA), technique for order of preference by similarity to ideal solution (TOPSIS) and linear programming (LP) problem has been used to develop a new model for the selection of 3PL vendor. First, DEA is used to evaluate the efficiency of each vendor according to the identified criteria. Second, TOPSIS is applied to rank the maximally efficient vendors. Finally, LP problem is stated and solved to ascertain the quantities to be allocated to each maximally efficient vendor in the context of multiple logistics provider. The proposed DEA–TOPSIS–LP (DETOLP) model is finally tested with real-time industry data for 3PL vendor evaluation and selection. The study, thus, proposes a three-step hierarchical technique for selection of 3PL vendor based on the multiple criteria decision-making approach. Findings The paper focuses on assessing the performance of 26 vendors using a combined approach of DEA, TOPSIS and LP. It is observed that vendor V4 outperforms all the considered vendors, which exactly corroborates with the present scenario within the company. Research limitations/implications Exclusion of qualitative criteria for 3PL vendor selection and the judgment of weights for TOPSIS can be considered as the limitations of the present work. The study has significant practical implications for organizations belonging to any sector or industry. It can help them in evaluating the existing 3PL vendors and selecting the most efficient among them. Originality/value This paper deals with a framework modeled for 3PL vendor selection. It is the first attempt to utilize an integrated approach, i.e. DETOLP model for evaluation and selection of 3PL. For assessment of the model, real data from an Indian company has been taken to analyze the result and compare it with the present scenario within the company.
 
Article
Purpose This paper aims to show that current Industry 4.0 maturity models primarily focus on manufacturing processes. Until now, research has been lacking with regard to outbound logistics, that is, the delivery process. This paper develops such a model. Design/methodology/approach Methodologically, this paper is grounded in design science research (DSR) and rigorously follows the model development guidelines presented by De Bruin et al. (2005). This work builds on current maturity models and original empirical research to populate and test the model. Findings The model appears to be applicable to describing the status quo of the digitization efforts in outbound logistics, developing a corporate vision for delivery logistics excellence and providing guidance on the development path. Research limitations/implications Thus far, the model has been applied only for a development stakeholder. For further validation, the authors are currently working on additional case studies to demonstrate the model’s applicability. Practical implications The developed model provides guidance for the digitization of an important value-adding activity in supply chain management: the delivery process. Originality/value To the authors’ knowledge, the proposed model is the first to explicitly consider the delivery process; therefore, it complements available approaches that focus on the manufacturing process. Moreover, the results show that the widely used Supply Chain Operations Reference model can serve as the basis for additional process maturity models.
 
Article
Purpose Cloud technology is extremely critical for the continuing progress of Industry 4.0 and it helps in pooling centralized information for the business. Further, it offers a platform for collaboration for improving the performance of the industry. This paper aims to investigate the factors affecting the implementation of cloud technology for boosting Industry 4.0 adoption in micro, small and medium enterprises (MSMEs) of the manufacturing sector. Design/methodology/approach A total of 14 enablers were considered for the case study which were obtained from the literature survey and shortlisted by the experts of the domain (academia and industries). The interpretive structural modelling (ISM) approach has been used as a methodology for exploring the relationships between the enablers. Matrices impact croises multiplication applique and classment (MICMAC) analysis has been carried out for the validation of the developed structural model. MICMAC analysis helps to identify driving power and dependency potential of all considered enablers. Findings The results of the investigation indicate that three factors, namely, system integration, project management and competitive pressure, were significant. These factors drive all other considered factors in the implementation process. Research limitations/implications The opinions of the experts from the industry and academia were analyzed for the development of the hierarchical model and these inputs could be biased. This investigation intends to help the decision makers in the effective adoption of the cloud and Industry 4.0 technologies and for the formulation of the efficient implementation policies. Originality/value The present study aims to focus on cloud technology as well as Industry 4.0 in the context of manufacturing MSMEs and none of the previous investigations analyzed the enablers that influence the adoption of cloud technology for boosting Industry 4.0, especially using the ISM approach.
 
Article
Purpose The concept of sustainable manufacturing has been adopted by manufacturing organizations to develop eco-friendlier products and processes. In recent times, industries are progressing toward Industry 4.0 (I4.0). Guided with smart intelligent devices, I4.0 can possibly decrease excess production, material movement and consumption of energy. If so, it is hypothesized that there is a good synergy between I4.0 and sustainability, which warrants an integrated approach for implementation. This amalgamation is termed as “Sustainable industry 4.0.” Hence, this paper aims to systematically identify and analyze the drivers for this integration. Design/methodology/approach This paper presents the analysis of 20 drivers identified from literature review for simultaneous deployment of I4.0 and sustainable manufacturing. Interpretive structural modeling (ISM) is used to derive the structural model for analyzing the causal association between drivers. Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis is being performed to group the drivers. Findings The results showed that the dominant drivers derived are societal pressure and public awareness (D18), government policies on support I4.0 (D12), top management involvement and support (D15) and government promotions and regulations (D16). Also, the MICMAC analysis revealed many driving, dependent, linkage and autonomous drivers. Research limitations/implications The opinion from experts with combined expertise on I4.0 and sustainability was obtained. The respondent size could be increased in future studies. Practical implications The study has been done based on inputs from industry practitioners. Managerial and practical implications are presented. ISM shows that the drivers for deploying sustainable I4.0 are highly inter-related. It also reveals the pre-requisites for each level of the drivers. Originality/value The idea of analyzing the drivers for sustainable I4.0 is the original contribution of the authors.
 
Input and output data
Article
Purpose This study aims to provide an estimation of carbon dioxide (CO 2 ) emission abatement costs in China’s industry sector during the period of 2006-2010, and additionally provide an ex-post estimation of CO 2 abatement cost savings that would be realized if carbon emission permits trading among different industry sectors of 30 provinces in China during the same period were allowed, to answer the question that whether the industrial carbon emission abatement cost can (partially) be recovered from carbon emission trading in China. Design/methodology/approach The joint production framework associated with the environmental technology is utilized for formulating the models for estimating abatement costs and simulating emission permits trading scheme. Several data envelopment analysis-based models that could deal with both the desirable and undesirable outputs within the above framework are utilized for abatement cost saving estimation. The weak disposability assumption and variable returns to scale assumption are applied in the modelling. Findings In China’s industry sector, during 2006-2010, the estimated CO 2 emission abatement cost was 1,842 billion yuan, which accounts for 2.45 per cent of China’s total industrial output value; the emission abatement cost saving from emission permits trading would be 315 billion yuan, which accounts for 17.12 per cent of the emission opportunity abatement cost; and additional 1,065.95 million tonnes of CO 2 emission reductions would be realized from emission permits trading, and this accounts for 4.75 per cent of the total industrial CO 2 emissions. Research limitations/implications The estimation is implemented at the regional level, i.e. the emission permits trading subjects are the whole industry sectors in different Chinese provinces, because of the data limitation in this study. Further estimation could be implemented at the enterprise level to provide a deeper insight into the abatement cost recovery from emission permits trading. Practical implications The estimation models and calculation process introduced in this study could be applied for evaluating the efficiency and effectiveness of pollutant emission permits trading schemes from the perspective that whether these market-based abatement policy instruments help to realize the potential abatement cost savings. Originality/value To the best of the authors’ knowledge, no study has provided the estimation of CO 2 emission abatement cost and the estimation of CO 2 abatement cost saving effect from emission permits trading for China’s industry sector. This study provides the first attempt to fill this research gap.
 
Article
Purpose This paper aims to determine the performance of the departments at Dr Zainoel Abidin Regional General Hospital, Banda Aceh, Indonesia, in 2016, based on the targets and realization of their work programs using balanced scorecard. Design/methodology/approach This study adopted qualitative and quantitative approaches. Findings The overall results of the performance appraisal using the balanced scorecard approach seen from the financial, internal business, customer and training and learning perspectives are good. Dr Zainoel Abidin Regional General Hospital has provided good services, and performance of its departments have generated the expected outcome, realized by the Hospital. Originality/value The novelty of the present study lies in its research model, where human resources (transformational leadership, organizational commitment and resource uniqueness) and financial management (business plans, budget and performance).
 
Impact of university reputation
Impact of increase in impatience, reputation and opportunity cost
Article
Purpose This paper aims to study students' strategic behaviors for increasing their job prospect in response to university administrators' moves for lifting up institutional reputation in the academia. Design/methodology/approach A Stackelberg differential game is used to study this strategic interplay between administrators and students. In this game, an administrator maximizes institutional quality to build university reputation while student maximizes grades to increase their job prospects. Therefore, administrators being the leader move first while students set strategies for maximizing their objective function by following administrators' move. Findings The study produces several distinctive results by analyzing administrator–students’ strategic interactions. First, university administrators need to be sufficiently more impatient for building reputation by improving institutional quality than students’ impatience for increasing their job prospects to have feasible solutions. Second, students attempt to increase academic grades for making them more marketable in response to administrators’ additional efforts for increasing their students’ job prospects. Third, exogenous increase in university reputation improves institutional quality and students’ job prospects without affecting their academic grades. However, increase in job prospects motivates students to increase their grades. Fourth, administrators’ too much impatience for increasing university reputation could inflate students’ grade, reduce job prospect and degrade institutional quality. Fifth, an exogenous rise in students’ impatience improves institutional quality and students’ job prospects but reduces students’ grades. Finally, the exogenous increase in opportunity cost of securing good grade degrades institutional quality, thus reducing further job prospects. Therefore, administrators’ positive but moderate impatience for reputation will improve students’ academic performances, institutional quality and job prospects. Originality/value To the best of the authors’ knowledge, this is the first study to analyze students’ strategic responses for improving their job prospects in response to administrators’ actions for enhancing university reputation. It helps administrators to design an effective framework for building university reputation in the academic market through improving institutional quality and expanding job markets for their students.
 
Article
Purpose This study aims to investigate the impact of new technologies on parameters of organizational behavior and evaluate their determining role of technology maturity and readiness of staff in the digital readiness. Design/methodology/approach This study has obtained an integrated model of technology’s effect on staff’s organizational behavior considering digital readiness level by using system dynamics is developed. In this model, the effects of new technologies entry on organizational behavior variables are analyzed in different layers, and the result of this impact on the consequent of a bank organizational behavior and each indicator is examined separately in different scenarios. In determining the indicators and their significant coefficients, the viewpoints of banking experts and professionals in organizational behavior have been considered. Findings As a result of our surveys, five technology effects, without intermediaries, were obtained, which are automation, learning, streamlining repetitive jobs, addiction to technology and reducing face-to-face contact. Each of these factors would make a chain of side effects. In a way that, ultimately, their positive or negative effects on productivity and consequently on organization profits appear. The result indicates technology has effects on important behavioral factors such as stress, motivation, organization values and personal satisfaction. Indicators, which are formed by positive or negative factors, are being upgraded or downgraded. Therefore, managing negative cycles and developing positive cycles can be considered as one of the major banking concerns for controlling IT effects on its organizational behavior of human resources. Originality/value There is little academic remarkable literature on clarifying the effects of digitalization on employee's behavior in an organization, this research offers managers and organizations a model of influential factors that need to be taken into account by managers when they encounter new technologies. This study’s proposed analysis is useful to improve the efficiency and productivity of the organization, and alongside this, it is effective for the digital transformation process. This study fills previous research gaps in the academic context related to the practical studies that relied on digital maturity.
 
Article
Purpose Technology presents e-commerce as an alternative buying and selling place that is accepted by the public. The high growth of e-commerce has an impact on the sustainability of both the economic dimension, the social dimension and the environmental dimension. Indonesia is the country with the fastest-growing e-commerce but also has the second-largest plastic waste in the world. The synergy of sustainability for e-commerce is an interesting and awaited innovation. This is because sustainability has become the responsibility of all countries in the world. Design/methodology/approach A theoretical understanding of the context of sustainability in e-commerce separately focuses on a company perspective and the use of green products from a consumer perspective. It requires the involvement of e-commerce stakeholders as a whole to get comprehensive research results. The use of qualitative research methods with exploratory approaches is used in this study to reveal the concept of sustainability in e-commerce in Indonesia. Findings This study found similarities in the topic of acceptance of sustainability in e-commerce with a unified theory of acceptance and use of technology (UTAUT) including performance expectancy, effort expectancy, facilitating conditions, social influence and habits. Changes to the variables were revealed due to changes in the e-commerce phase. The variable trust is in the introduction phase and builds trust in e-commerce. Currently, in Indonesia, the e-commerce phase is in a phase of growth and value formation. Habit creation and dependence is a requirement for value formation. Several new topics were proposed in this study, namely, awareness, security, logistics and user interface and user experience (UX). The establishment of an e-commerce identity through UX clearly shows its target market. The e-commerce phase and the topics involved in it can become a reference for e-commerce regulation-making in Indonesia. Research limitations/implications This study is limited to e-commerce in Indonesia with data processing limited to February 2020. Practical implications The results of this study provide an overview of increasing the intention to use e-commerce through human acceptance and engineering dimensions. This research also reveals the stages of e-commerce in Indonesia that can be used as a reference for determining the right regulations for e-commerce and the trade-offs for sustainability. Originality/value This study produces additional references to the intention to use technology by completing the UTAUT model. This study reveals changes in variables in perceived value that are interesting for further research along with technological developments and changes in people’s habits. Exploration carried out can add references to the application of sustainability in e-commerce, especially in developing countries.
 
Multi-phase decision process
Criteria for software quality
Modified model with level 1 priorities
Article
Purpose ‐ Due to the increasing complexity of decision environments, suitable multi-criteria methods are gaining importance for the decision support function in management accounting. The analytic hierarchy process (AHP), a well-known and established OR method for solving complex decision settings, is accompanied by the ongoing development of suitable software solutions. Especially for practical issues, software support can reduce barriers to applying AHP and can enhance acceptance by managers. For this reason, five heterogeneous software products are evaluated from a management accounting perspective. The paper aims to discuss these issues. Design/methodology/approach ‐ Based on the increasing relevance of AHP and the major changes in the field of AHP software solutions, the study of Ossadnik and Lange was replicated, with modifications. Five leading software products that use AHP were selected and evaluated with regard to their quality for solving decision problems. Pairwise comparisons were generated and integrated into an AHP-based decision model. The relevant criteria contained in this model were developed from the international standard norm for software evaluation. Findings ‐ In addition to revealing the necessity for further research on the development of appropriate software for multi-criteria decision problems, the result also shows that, under certain assumptions, "?Make It Rational" is the preferred software product. Practical implications ‐ Originating from different demands, the evaluation reveals the strengths and weaknesses of various software solutions for practical purposes. Originality/value ‐ This study shows that characteristics of software products using AHP vary, enabling users to select an appropriate software solution.
 
Article
Purpose – The purpose of this paper is to allocate marketing budgets in complex environments, where data are scarce and management judgment is available. In this research, marketing budgets are allocated, to maximize customer equity as a long-term profitability measure. Design/methodology/approach – The researchers provide a model for allocation of marketing budgets based on both decision calculus and econometric models and combine it with the concept of Markov chain model to cope with data scarcity. Dynamic programming is used to find the optimal solution. Findings – The authors examine the model in telecommunication industry. Applicability of the model is supported by an illustrative example. To allocate marketing budgets, researchers consider three strategies for each period: do nothing, retention-focused strategy and acquisition-focused strategy. The results show the applicability and effectiveness of the model to find the best strategy. Research limitations/implications – As the suggested approach is based on management judgment, it is useful in situations, as the authors have experts or experienced managers to achieve reliable data. In situations which the authors do not have access to experienced managers, the results may be unreliable. Practical implications – The suggested approach is useful in situations of data scarcity, where experienced managers are accessible. The researchers have focused on telecommunication industry cases; however, the model is useful in other industries like the insurance industry. Originality/value – The main contribution of the research lies in the suggestion of a new approach to allocate marketing budgets in data scarcity situations in multi-period planning horizons. The researchers use both decision calculus and econometric tools to find the transition matrices of marketing plans.
 
Article
Purpose The purpose of this paper is to propose a modified model in multi-stage processes when there are intermediate measures between the stages and in this sense, the new efficiency scores are more accurate. Conventional data envelopment analysis (DEA) models disregard the internal structures of peer decision-making units (DMUs) in evaluating their relative efficiency. Such an approach would cause managers to lose important DMU information. Therefore, in multistage processes, traditional DEA models encounter problems when intermediate measures are used for efficiency evaluation. Design/methodology/approach In this study, two-stage additive integer-valued DEA models were proposed. Three models were proposed for measuring inefficiency slacks in each stage and in the system as a whole. Findings Three models were proposed for measuring inefficiency slacks in each stage and in the system as a whole. Originality/value The advantage of the proposed models for multi-stage systems is that they can accurately determine the stages with the greatest weaknesses/strengths. By introducing an applied case in the Iranian power industry, the paper demonstrated the applications and advantages of the proposed models.
 
Change in values of objective functions by changing the available amount of resources
Change in values of objective functions by changing the tolerable return risk level
Change in values of objective functions by simultaneous changes in the available amount of resources and tolerable return risk level
Change in values of objective functions by simultaneous changes in the available capital, available amount of resources and tolerable return risk level
Article
Purpose This study aims to deal with a project portfolio selection problem aiming to maximize the net present value of the project portfolio and minimize the resource usage variation between successive time periods. Design/methodology/approach A bi-objective mixed integer programming model is presented under resource constraints. The parameters related to outlays and net cash flows of existing and new projects are considered to be uncertain. An augmented ε -constraint (AUGMECON) method is used to solve the proposed model, and a fuzzy approach is used to find the most preferred Pareto-optimal solutions among those generated by AUGMECON method. The effectiveness of the proposed solution method is compared with three other multi-objective optimization methods. Finally, some sensitivity analyses are performed to assess the effect of changing a number of parameters on the values of objective functions. Findings The proposed approach helps corporations make optimal decisions for rebalancing their project portfolio, through launching some new candidate projects and upgrading some of the existing projects. Originality/value A novel bi-objective optimization model is proposed for designing a project portfolio problem under budget constraints and profit risk controls. Two types of projects including existing and new projects are considered in the problem. Minimization of resource usage variation between successive periods is considered in the model as one objective function. An AUGMECON method is used to solve the proposed bi-objective mathematical model. A fuzzy approach is applied to find the best Pareto-optimal solutions of AUGMECON method. Results of the proposed solution approach are compared with three other multi-objective decision-making methods in different numerical examples.
 
Article
Purpose Sustainable supply chain management (SSCM) concepts have received immense attention in the recent past in both academia and industries. Especially, manufacturing industries in developing countries realize the importance of adopting sustainability concepts in their supply chain. The SSCM adoption has not been to the same level across different manufacturing sectors and hence a single implementation framework will not have the same effect across sectors. This paper aims to compare the adoption level of 25 SSCM practices across three major manufacturing sectors, namely, automobile, electronics and textile, in an emerging economy, India. Design/methodology/approach A questionnaire-based data collection technique is used to obtain adoption levels of each of the identified SSCM practices on a five-point Likert-type scale with “1” representing not considering presently to “5” indicating successful implementation. Second, a hypothesis is framed and tested to compare the adoption levels across sectors using a one-way single-factor ANOVA followed by a post hoc test by Tukey’s test. Findings The results derived suggest that though the industries across different sectors are in the course of adopting SSCM practices, the level of adoption is found to be not the same. The textile sector has adopted the least, and the electronic sector edges ahead of the automobile sector in terms of successful transformation to SSCM. Originality/value This study focuses on the differences and similarities in the adoption of policies in the automobile, electronics and textile sectors using statistical data analysis tools. A total of 25 individual practices are identified from existing literature and classified into six groups, namely, management, supplier, collaboration, design, internal and society, based on their similarities. Based on a detailed questionnaire survey with industrial experts in relevant fields as respondents, the adoption levels of practices are rated individually and categorically.
 
Article
Purpose – This paper aims to understand and identify the various barriers in adopting new telecom services in rural areas for improving the penetration and revenue of the telecom companies. These barriers are modeled to study their inter-relationships and prioritize them for strategizing appropriate management action plans. Design/methodology/approach – Delphi technique has been used to form a consensus with the telecom managers working in rural areas to finalize the barriers. An integrated Interpretive Structural Modeling–Analytic Network Process (ISM–ANP) approach has been adopted to establish the complex relationships, cluster the relationships, to understand and prioritize the telecom service adoption barriers. Findings – The major contribution of this research is imposing directions and dominance of various barriers to promote better adoption of new telecom-based mobile services in rural areas. The proposed integrated method can aid in decision making by providing more informative, accurate and a better choice than using either ISM or ANP in isolation. Research limitations/implications – The generalizabilty of these research findings is limited, as it was generated specific to rural telecom service adoption barriers in Indian context. Because decision-making problems are usually complex and ill-structured, every decision is based on the decision-maker’s expertise, preferences and biasness of the experts who showed their interest to participate in the research. Practical implications – This paper forms the basis of identifying the reasons for poor adoption of telecom-based mobile services in rural India. This study would help the telecom companies and the managers to understand and develop strategies to target the rural audience by introducing action plans and innovative mobile services to overcome the identified barriers. By applying the proposed methodology, telecom companies can classify and prioritize their action plans as short-, medium- and long-term plans to systematically overcome the identified barriers. Originality/value – This paper provides a base for understanding various factors that affect the adoption of telecom-based mobile services. It demonstrates the use of an innovative approach to develop an integrated model to understand the barriers.
 
Article
Purpose This paper aims to propose that the socio-technical perspective is under-represented when appraising the adoption potential of renewable energy technologies (RETs) in late-industrialising countries and that this results in under-adoption. It also aims to identify a methodological approach that allows the socio-technical perspective to be integrated into management decision-making, alongside the more typical economic appraisal methodology. Design/methodology/approach A case study and novel mixed-methodology approach is used, which applies the diffusion of innovations framework, innovation system (IS) framework and system dynamics modelling (SDM) alongside traditional economic modelling and appraisal techniques. This approach is used to assess the adoption potential of solar photovoltaic (PV) and diesel water pumping systems in the wildlife conservation sector and surrounding rural communities in Kenya. The case study approach tests the merits of the mixed-methodology approach. Findings The life-cycle costs of solar PV water pumping systems are lower in nearly all financing and utilisation scenarios; offer additional social, technical and environmental benefits; and the conditions exist for greater adoption. The use of an integrated diffusion of innovations and IS framework generates significant qualitative data that can support management decision-making. The use of SDM techniques aid conceptualisation of the community economic, water and institutional systems into which water pumps may be diffused and provide a starting point for formal SDM simulation. The results suggest that these techniques capture the socio-technical perspective well and, when used alongside traditional project appraisal approaches, produce more complete information with which to support management decision-making. Originality/value This mixed-methodology approach could be used by practitioners to increase the diffusion and adoption of RETs in more complex contexts in late-industrialising countries. The emergent theory built through the case-study approach should be tested further to assess the merits of applying these techniques to support RET management decision-making in other contexts and more broadly.
 
Article
Purpose This paper aims to propose a novel hybrid-decision-making trial and evaluation laboratory-K means clustering algorithm as a decision-making framework for analyzing the barriers of green computing adoption. Design/methodology/approach A literature review is conducted to extract relevant green computing barriers. An expert elicitation process is performed to finalize the barriers and to establish their corresponding interrelationships. Findings The proposed approach offers a comprehensive framework for modeling the barriers of green computing adoption. Research limitations/implications The results of this paper provide insights on how the barriers of green computing adoption facilitate the adoption of stakeholders. Moreover, the paper provides a framework for analyzing the structural relationships that exist between factors in a tractable manner. Originality/value The paper is one of the very first attempts to analyze the barriers of green computing adoption. Furthermore, it is the first to offer lenses in a Philippine perspective. The paper offers a novel algorithm that can be useful in modeling the barriers of innovation, particularly, in green computing adoption.
 
Article
Purpose This paper aims to develop a parsimonious and innovative model that captures the dynamics of new product diffusion in the recent high-technology markets and thus assist both academicians and practitioners who are eager to understand the diffusion phenomena. Accordingly, this study develops a novel diffusion model to forecast the demand by centering on the dynamic state of the product’s adoption rate. The proposed study also integrates the consumer’s psychological point of view on price change and goodwill of the innovation in the diffusion process. Design/methodology/approach In this study, a two-dimensional distribution function has been derived using Cobb–Douglas’s production function to combine the effect of price change and continuation time (goodwill) of the technology in the market. Focused on the realistic scenario of sales growth, the model also assimilates the time-to-time variation in the adoption rate (hazard rate) of the innovation owing to companies changing marketing and pricing strategies. The time-instance upon which the adoption rate alters is termed as change-point. Findings For validation purpose, the developed model is fitted on the actual sales and price data set of dynamic random access memory (DRAM) semiconductors, liquid crystal display (LCD) monitors and room air-conditioners using non-linear least squares estimation procedure. The results indicate that the proposed model has better forecasting efficiency than the conventional diffusion models. Research limitations/implications The developed model is intrinsically restricted to a single generation diffusion process. However, technological innovations appear in generations. Therefore, this study also yields additional plausible directions for future analysis by extending the diffusion process in a multi-generational environment. Practical implications This study aims to assist marketing managers in determining the long-term performance of the technology innovation and examine the influence of fluctuating price on product demand. Besides, it also incorporates the dynamic tendency of adoption rate in modeling the diffusion process of technological innovations. This will support the managers in understanding the practical implications of different marketing and promotional strategies on the adoption rate. Originality/value This is the first attempt to study the value-based diffusion model that includes key interactions between goodwill of the innovation, price dynamics and change-point for anticipating the sales behavior of technological products.
 
Article
Purpose The purpose of this paper is to demonstrate the efficacy of decision analysis in determining the most efficient strategy for installing cable television in the residence halls of Bucknell University. Design/methodology/approach The decision analysis model compared five distinct approaches for achieving and maintaining a successful delivery of cable television service to students enrolled in this private, residential institution. For each alternative, the model incorporated installation costs, likelihood of installation failure, installation failure costs, likelihood of obsolescence and obsolescence-related costs. In addition to considering the trade-offs between cost, timing and riskiness of the various alternatives, a thorough set of sensitivity analyses was performed to gain insight into the parameters that most strongly influence this decision-making process. Findings The quantitative model advocated the adoption of the university’s data network as the mode for cable delivery. Sensitivity analysis further supported this notion. Practical implications The analysis of this problem incorporated the knowledge and judgments of senior administrators and staff members, thus demonstrating the critical contributions offered by subject-matter experts in advising, informing and launching successful decision analysis projects. Incorporating stakeholder viewpoints enhances model understanding and, eventually, model implementation. Decision analysis represents a powerful approach in communicating uncertainties and advising on the benefits of particular alternatives. Originality/value To the best of the researchers’ knowledge, this paper represents an initial attempt to investigate cable delivery options within a decision analysis framework.
 
Article
Purpose Higher level of customer satisfaction for halal products can be achieved by the effective adoption of halal certification through assessment and accreditation (HCAA). There are certain issues that seem detrimental towards the adoption of HCAA. The purpose of this paper is to identify the major barriers towards the adoption of HCAA and evaluate inter-relationships among them for developing the strategies to mitigate these barriers. Design/methodology/approach The barriers towards the adoption of HCAA are identified through an integrative approach of literature review and expert’s opinion. The inter-relationship among the identified barriers is evaluated using fuzzy-based decision-making trial and evaluation laboratory (fuzzy DEMATEL) technique, which categorises them into influential and influenced group. Findings The evaluation of inter-relationship among barriers using fuzzy DEMATEL indicates four influencing barriers and six influenced barriers towards the adoption of HCAA. Further, findings suggest an extensive government, and management support is vital in terms of commitment, resources and actions to realise the benefits attributed with HCAA. Research limitations/implications The inter-relationship among barriers is contextual and based on the perception of experts which may be biased as per their background and area of expertise. This study pertains to a specific region and can be extended to the generalised certification system. Originality/value The empirical base of the research provides the inter-relationship among the barriers towards the adoption of HCAA which can be effectively used as input in the decision-making process by producers, manufacturers and distributor. The policy maker can analyse the cause group and effect group of barriers to formulate policies that would help in the adoption of HCAA.
 
Article
Purpose The paper aims to study a strategy of advance selling with part payment (ADP) in which pre-ordering consumers are required to pay a portion of advance price first and then pay the rest in the spot period to complete the order. The authors compare the ADP strategy with strategies of advance selling with full payment (ADF) and no advance selling (NA) from the perspective of sellers. Design/methodology/approach The paper proposes a two-period pricing model with price-off promotion in the first period for a market consisting of consumers and a single seller. For each strategy (i.e. NA, ADF and ADP), solutions to the seller’s optimal order quantity in the spot period, optimal advance price and prepayment in the advance period are derived by backward conduction. Numerical study is also used to obtain straightforward insights. Findings Advance price of ADF is lower than that of ADP. Order quantity of ADF is higher than that of ADP. ADP brings more profit than the other two selling strategies, i.e. NA and ADF, when ADP’s implementing conditions are satisfied. While ADF is effective only when unit cost is low, ADP is applicable irrespective of whether the cost is low. Originality/value Existing researchers on advance selling mainly focus on the ADF strategy. The paper pays attention to different payment mechanisms in advance selling and steps further to propose a new form of advance selling, i.e. the ADP strategy. The effects of ADP on consumer’s purchasing behavior and seller’s marketing decisions are analyzed.
 
Two-stage DEA for competitive advantage analysis
Article
Purpose – This paper aims to develop a framework for competitive advantage by systematic quantitative methodology based on resource-based view and dynamic capability theory. Strategic agility was used as a dynamic capability. Design/methodology/approach – Data were collected from a survey aimed at manufacturing companies from five manufacturing industry in Semnan, Iran. A total of 102 questionnaires were received from 13 companies using convenience sampling. Fuzzy two-stage data envelopment analysis model (DEA) was used to analyse the data collected. Findings – The results indicate that there is close internal relationship among firm resources, strategic agility and competitive advantage, and their inherent relationship makes constant returns to scale (CRS) scores closer to 1. In most of the companies, the second process which transforms strategic agility to competitive advantage is the main cause for unsatisfactory performance in gaining competitive advantage. Originality/value – The innovation of this paper is in its model and method. There is no research has been ever done on the relationship among firm resources, strategic agility and competitive advantage. Moreover, to obtain a competitive advantage structure, DEA technique was adopted which is a new approach in this area.
 
Top-cited authors
Gordon Foxall
  • Cardiff University
Shumaila Y Yousafzai
  • Cardiff University
John Pallister
  • Cardiff University
Adamantios Diamantopoulos
  • University of Vienna
Zillur Rahman
  • Indian Institute of Technology Roorkee