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Agile Sustainability Revolutionizing Risk Management in Finance
Abstract
In today's rapidly evolving financial landscape, the integration of Agile principles with sustainability practices has emerged as a transformative approach to risk management. This chapter delves into how Agile principles enhance risk assessment and mitigation strategies, emphasizing adaptability and collaboration in the finance sector. By integrating sustainability considerations, financial institutions navigate environmental, social, and governance (ESG) risks more effectively. Through Agile methodologies and advanced technologies like AI, finance professionals anticipate and address emerging risks proactively. This chapter highlights the pivotal role of Agile Sustainability in reshaping risk management paradigms, promoting resilience, and driving sustainable value creation in the finance industry.
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Regulatory reporting stands transformed by artificial intelligence's advent, offering numerous advantages in precision, efficacy, and compliance. AI enabled tools empower financial institutions to streamline compliance practices and mitigate risks through enhanced reporting accuracy. This article examines applications of AI in regulatory reporting and their benefits. The article also explores AI's transformative impact on financial institutions' adherence to regulatory mandates. Furthermore, it underscores human expertise's pivotal role in developing AI-driven regulatory reporting systems. As regulatory landscapes evolve, integrating AI technology into regulatory reporting processes becomes imperative for financial institutions.
This paper explores the transformative potential of Artificial Intelligence (AI) in personalized marketing. It highlights how AI can analyze vast amounts of customer data to create targeted messages, recommendations, and real-time interactions that resonate with individual needs and preferences. This personalized approach fosters deeper consumer engagement, leading to increased satisfaction, brand loyalty, and business success. The paper discusses the future potential of AI in shaping personalized marketing experiences. However, responsible implementation will be paramount in ensuring a positive future for both brands and consumers. Enhanced version of the abstract incorporating additional insights, this paper delves into the transformative power of Artificial Intelligence (AI) in personalized marketing. It explores how AI algorithms can analyze a multitude of customer data points, including purchase history, website behavior, and social media interactions. This rich data empowers brands to create highly targeted messages, recommendations, and real-time interactions that resonate with individual customer needs and preferences. By fostering deeper consumer engagement, AI-powered personalization unlocks a pathway to increased customer satisfaction, brand loyalty, and ultimately, significant business growth. However, the paper acknowledges the ethical considerations that accompany AI implementation. Responsible data practices are paramount, ensuring data security and mitigating bias in AI algorithms to prevent discriminatory marketing practices. Transparency in how data is collected and used builds trust with consumers, fostering a mutually beneficial relationship. Looking ahead, the paper explores the vast future potential of AI in personalized marketing. Imagine AI-powered Chat bot offering personalized product recommendations in real-time, or virtual reality experiences tailored to individual preferences. The future of marketing lies in creating genuine connections with consumers, and AI provides the tools to personalize the customer journey at every touch point. However, navigating the ethical landscape and prioritizing responsible data practices will be crucial in ensuring a positive future for both brands and consumers. Keywords: Artificial Intelligence (AI), Personalized Marketing, Customer Engagement, Customer Data, Marketing Strategy.
The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation focuses on three primary research questions: the main research themes concerning ESG and AI in finance, the evolution of research intensity and interest in these areas, and the application and evolution of AI techniques specifically in research studies within the ESG and AI in finance domain. Eight archetypical research domains were identified: (i) Trading and Investment, (ii) ESG Disclosure, Measurement and Governance, (iii) Firm Governance, (iv) Financial Markets and Instruments, (v) Risk Management, (vi) Forecasting and Valuation, (vii) Data, and (viii) Responsible Use of AI. Distinctive AI techniques were found to be employed across these archetypes. The study contributes to consolidating knowledge on the intersection of ESG, AI, and finance, offering an ontological inquiry and key takeaways for practitioners and researchers. Important insights include the popularity and crowding of the Trading and Investment domain, the growth potential of the Data archetype, and the high potential of Responsible Use of AI, despite its low publication count. By understanding the nuances of different research archetypes, researchers and practitioners can better navigate this complex landscape and contribute to a more sustainable and responsible financial sector.
Green bonds play a pivotal role in promoting sustainability by channeling financial resources towards environmentally friendly projects, fostering a greener and more resilient future. This research investigates the role of “Green Bonds” in the attainment of Sustainable Development Goals (SDGs), focusing on two specific goals: climate action, represented by per capita carbon emissions (CO2), and clean energy, represented by per capita renewable energy production. Using data from 2007, when the first green bond was issued, up to 2021, we employed a one-step generalized method of moments (GMM) model to explore how green bonds impact global emission reduction and the increase in renewable energy production. The findings demonstrate that green bonds have a significant influence on both emissions and renewable energy production. Specifically, green bonds and renewable energy production have a positive and significant association, while emissions exhibit a negative relationship with green bonds. Our results reported a reduction in carbon emissions up to 0.8 tons, while an increase in renewable energy up to 66 kWh. Upon analyzing the data before and after 2015, we observe that prior to 2015, there was no significant effect of green bonds on emissions and renewable energy production. However, after 2015, green bonds substantially impacted both indicators. Furthermore, our results indicate that countries with higher green bond issuance are more likely to achieve their sustainability goals, particularly in terms of renewable energy production and carbon emission reductions. Conversely, countries with lower green bond issuance are struggling to attain their sustainability objectives in these areas.
Purpose: The purpose of this research is to investigate the adoption of agile methodologies in the context of product management and assess their impact on product development processes, organizational culture, and overall business performance. The study aims to provide valuable insights into the challenges, benefits, and best practices associated with implementing agile practices in product management, ultimately contributing to the enhancement of product management strategies in contemporary organizations. Methodology: Descriptive research enables the exploration of various variables, such as organizational size, industry, and cultural factors, which may influence the adoption of Agile. It allows for an in-depth analysis of these characteristics and their impact on Agile practices. Thematic analysis serves as a robust method for uncovering insights and patterns within qualitative data, allowing for a nuanced exploration of the adoption of agile methodologies in the realm of product management. It provides a systematic and transparent approach to data analysis, enabling the research to contribute valuable findings to the field. Findings: Identification of common obstacles and challenges faced by organizations during Agile adoption, such as resistance to change, cultural alignment, and scaling Agile beyond individual teams. Recognition of the benefits of Agile, including increased product innovation, faster time-to-market, improved customer satisfaction, and enhanced adaptability to changing market conditions. Exploration of the concept of hybrid product administration systems is highlighting the advantages and disadvantages of combining Agile and traditional methodologies. The examination of the impact of Agile on fostering creativity and innovation within product development teams is done. Unique contribution to theory, practice, and policy: The study enriches the theoretical understanding of agile implementation models, hybrid systems, and the relationship between agile practices and creativity within teams. It provides a foundation for further theoretical exploration in the field. The research offers practical recommendations for organizations seeking to adopt agile methodologies in product management, providing insights into overcoming challenges, achieving a balance in hybrid systems, and fostering a culture of collaboration and creativity. The findings have potential policy implications for regulatory bodies and governments interested in promoting agile adoption. The research suggests the need for industry-specific guidelines and government support to facilitate agile implementation and innovation.
Sustainability through digital transformation is essential for contemporary businesses. Embracing sustainability, micro-, small-, and medium-sized enterprises (MSMEs) can gain a competitive advantage, attracting customers and investors who share these values. Moreover, incorporating sustainable practices empowers MSMEs to drive innovation, reduce costs, and enhance their reputation. This study aims to identify how owners or senior managers of MSMEs can initiate a sustainable digital transformation project. A systematic literature review was carried out, including 59 publications from 2019 to 2023. As a result, this research identifies the first steps owners of MSMEs can take to begin the transition by identifying critical organizational capabilities necessary for successful transformation, explores the technologies that can support MSMEs in their sustainability goals, and emphasizes the significance of stakeholders in achieving a successful digital transformation journey. Firstly, owners or senior managers should change the organizational culture to support decisions and strategies focus on sustainability. Secondly, the leading role of stakeholders is in the innovation process that allows businesses to be more competitive locally and globally. Finally, big data is the technology that can provide the most significant benefit to MSMEs because it will enable analyzing data of all kinds and contributes disruptively to decision-making.
The energy sector is enduring a momentous transformation with new technological advancements and increasing demand leading to innovative pathways. Artificial intelligence (AI) is emerging as a critical driver of the change, offering new ways to optimize energy systems operations, control, automation, etc. Developing a competitive policy framework aligned with circular economy practices to adapt to the trends of the rapid revolution is crucial, shaping the future of energy and leading the sector in a sustainable, equitable, and impartial direction. This study aims to propose an AI-driven policy framework that aligns with the circular economy business model to address the transformation trend in the development of energy policies through a multidisciplinary approach. The study identifies key trends, various approaches, and evaluates the potential of AI in addressing the challenges. The AI-driven policy paradigm outlines a comprehensive framework and roadmap to harness the potential of AI through a forward-looking policy framework that considers the rapidly changing landscape and the essence of the circular economy. The proposed novel framework provides a roadmap for researchers, governments, and other stakeholders to navigate the future of energy and unlock the potential of AI for a sustainable energy future.
In the global trade economy, the degree of competition and differentiation among organizations working in the sector of Supply Chain Management (SCM) is expanding gradually. For companies, SCM operations are becoming more important than manufacturing, sales, and marketing activities, and new ways and methods are preferred for efficiency and performance. The agility (or agility phenomenon) is one of the applications that aids effective SCM operations in this context. Agile Supply Chain Management (ASCM) and the emergence of Industry 4.0 practices, in addition to offering a cost advantage and business performance improvement, are crucial in providing flexibility to companies and ensuring their survival in the era of Industry 4.0. Meanwhile, companies aim to deal with uncertainty and implement various risk-reduction strategies as part of effective SCM. In this context, the study lists the critical success factors of ASCM and selects the most appropriate risk reduction strategy for companies that manufacture and market rubber and plastic products with a corporate identity and conduct import and export business in Istanbul. For this purpose, the criteria and alternatives specified in accordance with the literature review and experts’ opinions are examined using Bipolar Neutrosophic Stepwise Weight Assessment Ratio Analysis (BN-SWARA) and Bipolar Neutrosophic Technique for Order of Preference by Similarity to Ideal Solution (BN-TOPSIS) methods. The ranking results are then discussed in line with the practical implications to provide managerial insights and decision aids. Finally, the main limitations are expressed in order to delineate useful future research directions.
We investigate approaches for the transformation of traditional top-down organizations into agile organization in the Financial Service Industry. These approaches are combinations of Scaled Agile Framework (SAFe©), Large-scale Scrum (LeSS), Disciplined Agile Delivery (DAD) and the Spotify tribes. All concepts have in common to follow an enabling leadership concept, which is different to hierarchical management principles and contrary to that is governed by self-leading teams. Based on the specific requirements of regulatory-driven programs, high-complexity, equally business value, high level of audit engagement, dispersed customer need, principal-agent conflict caused information asymmetries, we conclude that the existing four methodologies SAFe©, LeSS, DAD and the sportify tribe model do not fully adhere to the business needs for the transformation into agile organizations for globally distributed corporations. Based on the identified gaps the methodology is refined and enhanced. This leads to the creation of RegSafe 2 ©, the agile management control methodology to convert organizations into agile organizations. RegSafe 2 © is based on the agile framework and bundles in a mixed-method approach management control system, stakeholder and behavioral economics underpinnings. While management control system intends to align individual activities with organization goals, under agile philosophy self-governing and autonomous teams fulfill objectives set by the organization instead of micro-management. Under agile philosophy enabling leadership concepts are pursued, as teams are expected to self-govern and decide on solutioning without direct management control, which requires agile skilled employees and a commitment to co-work for a mutual goal. Agile transformation requires strong commitment by all involved parties and without a common agile mindset is difficult to accomplish within a short timeframe. Due to that agile transformed and non-agile non-transformed will need to cooperate, as long as not all part of organization are transformed into one model, which is also reflected by RegSafe 2 ©. This article has implications for practitioners and researchers on the transformation of agile organizations and program managers of regulatory-driven programs.
Institutional investors who commit to integrating environmental, social and governance (ESG) aspects into investment decisions require ESG data of sufficient quality. However, concerns have risen over a lack of quality in ESG data, as outlined by the Global Reporting Initiative. The lack of quality in ESG data deters institutional investors from using the data for investment decisions. This study outlines the ESG data reporting process and explores where in the process quality concerns emerge. Semi-structured interviews are applied with professionals involved in ESG data analysis and reporting of listed companies, a rating agency and institutional investors. The results show that current barriers to using ESG data include a lack of materiality, accuracy and reliability. Interviewees agree that access to data collected by governmental institutions is lacking, and that companies’ purchase of carbon credits raise questions about the reliability of ESG data. Companies hold contrasting views to the institutional investors on the useability of the data they disclose. The results enhance our understanding of the common and contrasting concerns about the lack of quality in ESG data. The results can be used as guide for companies, investors and regulators for actions to mitigate barriers related to the lack of quality in ESG reporting.
Industry 4.0 technologies provide critical perspectives for future innovation and business growth. Technologies like Artificial Intelligence (AI), Internet of Things (IoT), Big data, Machine Learning, and other advanced upcoming technologies are being used to implement Industry 4.0. This paper explores how Industry 4.0 technologies help create a sustainable environment in manufacturing and other industries. Industry 4.0 technologies and the crucial interrelationships through advanced technologies should impact the environment positively. In the age of Industry 4.0, manufacturing is tightly interlinked with information and communication systems, making it more scalable, competitive, and knowledgeable. Industry 4.0 provides a range of principles, instructions, and technology for constructing new and existing factories, enabling consumers to choose different models at production rates with scalable robotics, information, and communications technology. This paper aims to study the significant benefits of Industry 4.0 for sustainable manufacturing and identifies tools and elements of Industry 4.0 for developing environmental sustainability. This literature review-based research is undertaken to identify how Industry 4.0 technologies can help to improve environmental sustainability. It also details the capabilities of Industry 4.0 in dealing with environmental aspects. Twenty major applications of Industry 4.0 to create a sustainable environment are identified and discussed. Thus, it gives a better understanding of the production environment, the supply chains, the delivery chains, and market results. Overall, Industry 4.0 technology seems environmentally sustainable while manufacturing goods with better efficiency and reducing resource consumption.
The finance sector has a long track record of engaging with sustainability issues, and policymakers and sector representatives agree that a transition to sustainability needs to be mirrored by rapidly expanding financing. Based on in-depth interviews with a broad range of actors in the Swedish finance sector, we show that despite a strong recognition of the challenges, the sector remains cautious towards risk. We explore what motivates the sector and how to govern a faster transition and find that informants strongly believe that the sector cannot move any faster without further government intervention. The preferred policy is the use of generic tools such as CO2 taxes, or for the government to step in and mitigate the risk. We conclude that a more ambitious narrative on how the private and public sector can collaborate to share risk is needed, as it is unlikely that the finance sector will lead the way.
Kanban is a well-known agile method first implemented in Toyota's manufacturing process in the 1950s, later spreading across various industries and academic fields. It focuses on process and project improvement in different fields and emphasizes a team's ability to improve the efficiency of day-to-day activities by implementing the core practices (e.g., visualizing workflow, limiting work-in-progress, managing flow). The efficiency of day-to-day activities is crucial in every process, yet, recent times have called for a new out-of-the-box approach to address the challenges companies face. While the literature review presents efficiency improvements through the use of the core practices, one of the biggest problems while implementing Kanban is shown to be the setting of effective work-in-progress limits. This article addresses this issue and proves that the workflow does not exclusively depend on the work-in-progress limits—as the core practices suggest—but on determining the optimal relationship (solution) among the replenishment value, resource capacity, and work-in-progress limits. Such an approach ensures that the workflow pace on the Kanban board is sustainable by reducing the number of work items in queues as well as people's idleness. The proposed empirical approach runs a series of simulation scenarios aimed at helping to identify the optimal relationship among the three mentioned elements for generating a sustainable workflow pace and minimizing work/people's idleness.
This study analyses the impact of Spanish financial institutions’ risk profile on their contribution to the 2030 Agenda. Financial institutions play a significant role in ensuring financial inclusion and sustainable economic growth and usually incorporate environmental and social considerations into their risk management systems. The results show that financial institutions with less capital risk, with lower management efficiency and with higher market risk usually make higher contributions to the Sustainable Development Goals (SDGs), according to their sustainability reports. The novel aspect of the present study is that it identifies the risk profile of financial institutions that incorporate sustainability into their business operations and measure the impact generated in the environment and in society. The study findings have important implications for shareholders, investors and analysts, according to the view that sustainability reporting is a vehicle that financial institutions use to express their commitment to the 2030 Agenda and to higher quality corporate reporting.
Agile methodologies have emerged to challenge traditional ones and overcome their limitations. Increasingly, software development organizations are scaling agile practices in order to meet the requirements of the quickly changing and regularly developing business environment. The main objectives of this study are to investigate the main differences between the traditional project management methodologies and agile methodologies, as well as to identify some key advantages and challenges of applying agile development in a financial software environment. The findings clearly show that using Agile methodologies in a financial software development environment increases the efficiency and transparency of the development process, as well as the stakeholders’ satisfaction, but the project managers must know how to adapt different Agile frameworks to the given context of their organization.
Sustainability-related risks and risk management frameworks have been introduced in the literature to help project managers identify and manage critical risks influencing project sustainability. Theoretically grounded in the framework of Monte Carlo Simulation, this paper introduces and operationalizes a new process for prioritizing sustainability-related project risks using risk matrix data. Sustainability-related construction project risks have never been assessed relative to different confidence levels across the risk matrix-based exposure zones. The application of the proposed process on construction projects completed in the United Arab Emirates reveals that the conventional risk prioritization scheme undermines the importance of tail risks (unexpected events), whereas such risks are captured in the proposed process. In contrast to the most critical risks identified using the conventional scheme such as shortage of client’s funding, insufficient or incorrect sustainable design operation, and design changes, the proposed process prioritizes risks such as poor productivity of labor and equipment in sustainable construction, unreasonable tight schedule for sustainable construction, and poor scope definition of sustainable construction. The proposed process is generalizable to prioritizing risks influencing sustainability in international construction projects and beneficial for enhancing project sustainability as there is a huge uncertainty associated with sustainability-related risks.
Sustainability has evolved into one of the key topics for organizations and organizational researchers alike. To meet changing societal demands, organizations have to adapt their long-term strategies and incorporate environmental and social aspects into their product offerings and decision-making. However, at the same time companies must satisfy short-term profitability interests and demands from shareholders. An organization’s sustainability commitment, strategy, or view is impacted by several influential factors, e.g., by the top management commitment or stakeholder integration. These factors have largely been studied individually without linking them. As such, the following study aims at creating a holistic view and framework for organizational influences and on sustainability. The framework is validated by a comparison to industrial practice in interviews with sustainability managers from the chemical and automobile industry, which are both highly relevant in the context of sustainability. Interview results suggest that the identified influential factors attributed to the four framework layers organization, top management, project team and project are relevant for industrial representatives. The view on and impact of specific influential factors can vary between companies and industries. The study further gives insights into the actual status and future direction of the management of corporate sustainability (CS) in practice.
Sustainability risk management (SRM) is an approach that manages the broad spectrum of risks arising from sustainability issues such as climate change, resource depletion and natural catastrophes. SRM is an extension to Enterprise Risk Management (ERM) that aims to maximize environmental, social and economic performances for a company’s survival. In an SRM practice, knowledge management is a strategic resource for companies to sustain in the rapidly-evolved business environment. It provides a solution to address the unknown risks associated with environmental complexity. Thus, the aim of this study is to examine the moderating effect of knowledge management on the relationship between SRM critical factors (ERM bases and organizational resilience) and company survival among public listed companies (PLCs) in Malaysia. Partial Least Squares Structural Equation Modelling (PLS-SEM) technique is used to analyze the hypothetical model which is developed in this study. The result shows that knowledge management moderates the relationship between organizational resilience and company survival. This finding signifies that knowledge management is an important strategic resource to assist companies to develop effective risk management strategy. This will lead to better decision-making and risk controls which influence stakeholder value and company reputation. The study also finds that ERM bases and organizational resilience were significant towards company survival. Companies with strong ERM bases such as procedures, infrastructure and methods have higher chances of successful SRM implementation. Organizational resilience refers to the ability of a company to manage crises and disaster risks, which is crucial for a company’s survival. This study has both theoretical and practical implications. The result of this study provides relevant insights on the value of knowledge management to meet stakeholder expectations. It also provides a better understanding of the relationship between SRM implementation, its critical factors and company survival.
As a key facet of sustainable development, environmental, social and governance (ESG) discretion on stock market investment decision is gaining prevalence following the global financial crisis. ESG considers the sustainable return, risk reduction, and accountability aspects of investments. This study is an exploration of the individual stock market investors’ preferences for ESG issues and the influence that purpose of investment has on investment decision-making, by testing the investment horizon as a moderator. The theoretical background was taken from the theory of planned behavior (TPB), goal setting theory (GST), and the behavioral asset pricing model (BAPM). The study uses the sequential mix method of research, starting with an interview followed by a survey, which was conducted among individual stock market investors in Bangladesh, using simple random sampling. Structural equation modeling (SEM) analysis was carried out using Warp PLS version 6.0. The key findings of this study delineate the effect of ESG issues and the purpose of investment on investment decision-making. The contribution of the study signifies the moderating role of the investment horizon, which confirms the importance of the long-term horizon as a time and risk diversification factor. The sparse utilization of the United Nations Global Compact (UNGC) (2004) and Thomson Reuters Corporate Responsibility Index (TRCRI) (2013) as measurement scales in this study is mentioned. This study has made practical contributions for managers, investors, and regulators.
This article presents a bibliometric study of Risk Management in Scrum Projects. It was carried out an analysis involving the ISI Web of Knowledge and Scopus databases, identifying the main authors, countries and periodicals. It also identified the most cited authors by the analyzed articles, in addition to the keywords most frequently cited. These analyzes were performed using the reference maps, which were generated by CiteSpace® software, which offers a set of features to support bibliometrics. The objective was to identify the current scenario research of Risk Management applied in Scrum Projects in order to offer a consistent basis of information to researchers. The research verified that, despite the importance of the research topic, few scientific studies have been identified, which brings the need for new researches on the subject.
Intelligent and agile risk management is a proactive and adaptive approach to managing risks in organizations, including healthcare settings. It combines advanced technologies, data analytics, and agile practices to enhance risk identification, assessment, response, and monitoring. This approach leverages artificial intelligence, machine learning, and automation to gather and analyze data, predict potential risks, and support decision-making processes. By adopting intelligent and agile risk management, organizations can benefit from proactive risk identification, enhanced risk assessment accuracy, agile response strategies, improved decision-making, and optimized resource allocation. It also promotes continuous learning, stakeholder engagement, and a culture of continuous improvement. However, implementing intelligent and agile risk management comes with challenges, such as complexity, data security and privacy concerns, financial considerations, skill requirements, and the need for effective change management. To mitigate these risks, organizations should carefully plan and prepare for implementation, prioritize data security and privacy, conduct thorough cost-benefit analysis, address skill gaps, balance technology reliance with human judgment, ensure smooth integration, and establish ethical frameworks. By addressing these considerations, organizations can unlock the advantages of intelligent and agile risk management while mitigating potential risks and optimizing risk management outcomes.
Distributed Agile Software Development (DASD) is an amalgamation of Agile Software Development (ASD) with Distributed Software Development (DSD). Although DASD integrates the speed benefits of ASD with the cost benefits of DSD, however, it brings along various risk factors that arise due to the fact that both ASD and DSD works on a different set of principles. These associated risks must be addressed and managed well in time for the successful completion of the project. This paper reviews the current literature and presents the current challenges of Risk Management in the DASD environment. This paper also determines 71 risk factors associated with DASD and analyses them based on their causes and sources. Further, these risk factors are segregated into 11 different categories. Timely management of these risks may reduce the uncertainty of project failure in the DASD environment.
Purpose
– The purpose of this study is to investigate how the social licence to operate (SLO) concept is currently perceived and communicated during stakeholder engagement, as an extension of corporate social responsibility (CSR). To ensure an applied exploration of SLO, this paper focused on the wind industry.
Design/methodology/approach
– Telephone interviews were conducted with 18 wind industry representatives responsible for stakeholder engagement in Australia. Questions focused upon understanding of consultation and SLO, perceptions of SLO in practice, and experiences regarding community engagement.
Findings
– SLO is broadly understood by the case study wind industry representatives as majority acceptance held by community and other stakeholders, although no common definition was expressed. This indicates that the concept has not transferred clearly or directly to the wind industry. Despite this, the benefits of seeking an SLO through consultative and ongoing communication practices were recognised across the wind industry as a positive risk mitigation strategy.
Research limitations/implications
– Future research could examine the understanding and communication approaches of SLO in other industries, cultures and geographic locations.
Practical implications
– It appears the wind industry intends to seek an SLO more broadly from the Australian public, beyond specific projects. This is likely to occur within the context of increased scrutiny on the performance of many industries and by the changing expectations and demands of communities.
Social implications
– Some wind corporations were considered to have previously conducted poor or shallow consultation, and this was perceived to have negatively affected the reputation of the wider industry. Mismanagement of expectations prior to the development phase was of particular concern to interviewees. Given this, an SLO could be put at risk by the poor or insufficient engagement and communication processes and reputation of their predecessors.
Originality/value
– The key contribution of this study is to inform CSR practices that seek to engage and maintain high stakeholder support through an SLO approach, where corporate communication is vital.
Previous research has considered combining different decision-making approaches to be critical to achieve flexibility in Project Portfolio Management (PPM). Lacking flexibility, i.e., making decisions only by rational and formal approaches, might lead to a deficient balance between different types of ideas and projects, and this may lead to innovation opportunities being missed. However, the challenges that decision makers might face in achieving that flexibility have not been investigated thoroughly. In an interview study of three industrial companies, we explored how different decision-making approaches are combined in PPM. We found that rational and formal decision-making processes are experienced as more legitimate than informal and non-rational ones. Decision makers deal with legitimacy by certain mechanisms that allow them to bypass high accepted approaches and legitimizing decisions made by low accepted ones. We discuss how these mechanisms, while contributing to achieving flexibility, might also cause a bias in decisions and destabilization in resource allocation.
This paper argues that solely depending on short-term financial performance indicators to justify the benefits of JIT implementation is very misleading and could harm a company’s future long-term survival. The empirical study presented in this paper investigated the effect of (JIT) implementation on the use of operation performance measures. Furthermore, the effect of the JIT implementation and the use of the operating performance measures on firms’ financial/growth performance, as perceived by the managers, was examined. These effects were measured using path analysis to show direct and indirect effects of JIT practices on the other two variables. Analyses indicate that, although correlations do exist between JIT practices and managerial perceptions of a firm’s financial performance, the relationships are mostly the result of spurious effects. Direct and indirect effects realized from the JIT practices on financial/growth performance are almost non-existent.
Axa Retrieved May 30
- Axa
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- M. O.Ahmad