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To: evaluate Prospect Theory and Cumulative Prospect Theory as functional models of decision making and risk within various contexts; compare and analyze risk models and decision‐making models; evaluate models of stock risk developed by Robert Engle and related models; establish whether the models are related and have the same foundations; relate risk, decision making and options theory; and develop the foundations for a new model of decision making and risk named “belief systems”.

Critiques existing academic work in different contexts. Analyzes the shortcomings of various measures of risk, and group decision making, which was not addressed in developing Prospect Theory and Cumulative Prospect Theory. Develops the characteristics of a mew model for decision making and risk named “belief systems”, and then differentiates it from belief networks.

Decision making is a multi‐factor, multi‐dimensional process that often requires the processing of information, and thus, it is inaccurate to impose rigid models in decision making; the existing metrics for quantifying risk are inadequate; Prospect Theory and Cumulative Prospect Theory were developed using questionable methods and data, and are impractical; the analysis of probabilistic insurance and most of the theories and “effects” developed by Kahneman and Tversky's articles are invalid and impractical; Prospect Theory, Cumulative Prospect Theory, Expected Utility Theory, and market‐risk models are conceptually the same and do not account for many facets of risk and decision making; risk and decision making are better quantified and modeled using a mix of situation‐specific dynamic, quantitative and qualitative factors; belief systems can better account for the multi‐dimensional characteristics of risk and decision making.

Areas for further research include: development of dynamic market‐risk models that incorporate asset‐market psychology, liquidity, market size, frequency of trading, knowledge differences among market participants, and trading rules in each market; and further development of concepts in belief systems.

Decision making and risk assessment are multi‐criteria processes that typically require some processing of information, and thus cannot be defined accurately by rigid quantitative models; Prospect Theory and Cumulative Prospect Theory are abstract, rigid, and are not practical models for decision making; and existing market‐risk models are inaccurate, and thus the international financial system may be compromised.

The issues discussed are relevant to government regulators, central banks, judges, risk managers, executives, derivatives regulators, stock exchange regulators, legislators, psychologists, boards of directors, finance professionals, management science/operations research professionals, health‐care‐informatics professionals, scientists, engineers, and people in any situation that requires decision making and risk assessment.

The paper provides a comprehensive overview of the biases in inventory decisions, under the umbrella of behavioural operations, considering research findings that used experimental methods. Research in this field has gained traction but, to the best of our knowledge, review articles that summarize these research findings are scarce. Hence, there is a need to synthesize the anomalies and biases reported in inventory decision-making literature to gain a more integrated understanding.

This study reviews themes relevant to inventory and behavioural operations management from the articles published in recognized top-tier journals during the period between 2000 and 2020 with an aim to build a classification framework. Further, using a systematic review procedure, the relevant research studies are divided into sub-sections and appropriate search strategies are adopted to pleat more information on inventory ordering biases.

This study presents a classification framework by highlighting the factors influencing the biases in inventory decisions and describes the effects of utility preferences on the decision-making behaviour. It highlights the inventory ordering pattern under unconventional settings and also for different supply chain settings. This systematic review helps in identifying the research gap and in giving directions for future researchers.

The study presents a systematic review and detailed analysis of the research in inventory decision making through a behavioural lens. The study shows a clear direction of progress over the years, and implies new directions for looking beyond placing orders and for moving towards a more integrated approach while making supply chain decisions. It will be useful for researchers and practitioners working on newsvendor decisions, supply chain contracts, behavioural economics, behavioural operations management, bounded rationality theory and experimental economics.

Knowledge has been considered a crucial organizational asset for gaining competitive advantages. It is critical for a firm to maintain a knowledge composition that is productive. This study aims to examine the applicability of the diversity–stability principle in ecology to knowledge management and further investigate the impact of knowledge diversity on firm performance.

A theoretical framework for knowledge diversity and firm performance is proposed; a questionnaire survey was conducted to evaluate the research framework. Fifty-eight valid responses from experts were collected to measure knowledge strength and diversity of 20 enterprises in four industries, and financial indexes of the 20 enterprises from 2008 to 2012 were collected to analyze the research model.

The results show that higher information technology (IT) capabilities in a firm lead to higher levels of knowledge strength and diversity. The strength and diversity of knowledge in a company can improve average company performance and reduce performance variations.

This paper presents a new perspective that applies the ecological concept of diversity to examine the value of knowledge in organizations. The findings expand our understanding of the role of IT and knowledge in organizational performance. A limitation is that the sample size is relatively small, which may limit the generalizability of the findings.

CEOs and chief knowledge officers can apply the findings herein to assess their organizational knowledge profiles and maintain a healthy knowledge ecology in strategic planning. They should be aware that both knowledge strength and knowledge diversity are crucial to the stability of firm performance.

The ecological view of knowledge management stresses the importance of maintaining a healthy intensity and diversity of knowledge at the macro level and indicates a new direction for knowledge management.

This study aims to investigate how relatively weaker manufacturers respond to the dominance of stronger suppliers and/or customers. The study also analyzes how the competitive intensity perceived by manufacturers moderates their responses to powerful chain partners.

Using hierarchical regression, data from 1,417 manufacturing companies sampled from the fifth and sixth versions of the International Manufacturing Strategy Survey were analyzed.

This study found that relatively weaker manufacturers often adopt exploration strategies to countervail the dominance of suppliers and adopt exploitation strategies to deal with more powerful customers. In dealing with both dominant suppliers and customers, relatively weaker manufacturers are prone to adopt exploration and exploitation strategies simultaneously and hence become ambidextrous. Furthermore, the link between dominance in supply chains and the exploration (exploitation) strategy is strengthened (weakened) as market competition perceived by manufacturers intensifies.

The contribution of this paper is multi-folds. First, this paper develops and test a novel theoretical model on how relatively weaker manufacturers create tailored strategies to defend their positions in the supply chain. Second, it integrates resource dependence theory and organizational learning theory to propose that relatively weaker manufacturers could use a unique configuration of exploration and exploitation strategies to counteract the dominance of their suppliers and customers. Third, it investigates supply chain power by considering the manufacturers’ upstream and downstream powerful partners together, rather than individually and fourth, it reveals that relationships linking supply chain power to manufacturers’ tailored strategies are contingent on competitive intensity.

This paper deals with external audits, which are now commonly used in many industries (e.g. food, automotive and electrical). This study aims to assess whether a given organization meets the specific criteria. If the audit ends with a positive result, information about it is provided to selected interested parties, e.g. clients or contractors. Credibility is pivotal in adding value for all interested parties within the audit processes. This study seeks the factors which, in the opinion of the audited enterprises, have the most decisive impact on the credibility of external audits.

In keeping with the extant literature, research questions were developed regarding the factors influencing the credibility assessment of external audits. Data collected from 100 companies in the Polish food sector were used to construct the model and carry out statistical analyses. Linear regression analyses were also applied to determine the key factors influencing the credibility of audits.

This study is part of the research trend on the rationality of external audits and certification of quality management systems. This paper identifies nine main factors shaping the credibility of external audits. Two of them have the most decisive influence on credibility. The first one is the professional audit method (procedure). The second factor is the auditor’s knowledge of the specificity of the audited area.

This study did not consider the impact that the image/credibility of the organization represented by the auditors may have on the reliability of audits. This is one of the fundamental limitations that should be considered when analyzing the obtained results. To recognize this type of dependence, additional research should be carried out. Another limitation is that the research covers the food industry only. It would be interesting to know the situation in other types of industries.

This paper looks at the possibility of increasing the added value for audited enterprises. The proposed model can be used by managers of organizations conducting external audits and auditors to effectively use resources for process improvement, influencing the maximization of credibility of activities in the area of conformity assessment.

The originality of this study lies in adopting the perspective of audited enterprises in assessing the credibility of audits. To the best of the authors’ knowledge, this is the first study that adopts this approach. This paper contributes to the literature, particularly to better understand audited enterprises’ behavior (trust in audit results, satisfaction with audits, etc.).

To: evaluate Prospect Theory and Cumulative Prospect Theory as functional models of decision making and risk within various contexts; compare and analyze risk models and decision‐making models; evaluate models of stock risk developed by Robert Engle and related models; establish whether the models are related and have the same foundations; relate risk, decision making and options theory; and develop the foundations for a new model of decision making and risk named “belief systems”.

Critiques existing academic work in different contexts. Analyzes the shortcomings of various measures of risk, and group decision making, which was not addressed in developing Prospect Theory and Cumulative Prospect Theory. Develops the characteristics of a mew model for decision making and risk named “belief systems”, and then differentiates it from belief networks.

Decision making is a multi‐factor, multi‐dimensional process that often requires the processing of information, and thus, it is inaccurate to impose rigid models in decision making; the existing metrics for quantifying risk are inadequate; Prospect Theory and Cumulative Prospect Theory were developed using questionable methods and data, and are impractical; the analysis of probabilistic insurance and most of the theories and “effects” developed by Kahneman and Tversky's articles are invalid and impractical; Prospect Theory, Cumulative Prospect Theory, Expected Utility Theory, and market‐risk models are conceptually the same and do not account for many facets of risk and decision making; risk and decision making are better quantified and modeled using a mix of situation‐specific dynamic, quantitative and qualitative factors; belief systems can better account for the multi‐dimensional characteristics of risk and decision making.

Areas for further research include: development of dynamic market‐risk models that incorporate asset‐market psychology, liquidity, market size, frequency of trading, knowledge differences among market participants, and trading rules in each market; and further development of concepts in belief systems.

Decision making and risk assessment are multi‐criteria processes that typically require some processing of information, and thus cannot be defined accurately by rigid quantitative models; Prospect Theory and Cumulative Prospect Theory are abstract, rigid, and are not practical models for decision making; and existing market‐risk models are inaccurate, and thus the international financial system may be compromised.

The issues discussed are relevant to government regulators, central banks, judges, risk managers, executives, derivatives regulators, stock exchange regulators, legislators, psychologists, boards of directors, finance professionals, management science/operations research professionals, health‐care‐informatics professionals, scientists, engineers, and people in any situation that requires decision making and risk assessment.

Over the last ten years scores of methodologies have emerged in management science/operations research/statistics that employ techniques such as mathematical programming, simulation, artificial intelligence, and clustering to convert a flexible manufacturing system into a cellular one. Based on a real‐life case that involved over 1,000 components and 3,000 operations, related to a world‐class furniture manufacturing company, finds that the somewhat outdated King’s algorithm, after partial linearization, works as well as the other sophisticated techniques in terms of speed and problem size. Drives home the point that a shift to cellular configuration from functional layout results in across the board savings in material movement, setup times, hilo moves, WIP, work area and in manufacturing leadtime. The company under study benefited to the tune of $164,000 per year from switch to single cell. The projected savings are expected to exceed $700,000 per year when the reconfiguration is completed.

The two most used citation impact indicators in the assessment of scientific journals are, nowadays, the impact factor and the h-index. However, both indicators are not field normalized (vary heavily depending on the scientific category). Furthermore, the impact factor is not robust to the presence of articles with a large number of citations, while the h-index depends on the journal size. These limitations are very important when comparing journals of different sizes and categories. The purpose of this paper is to propose an alternative citation impact indicator, based on the percentage of highly cited articles in the journal.

This alternative indicator is empirically compared with the impact factor and the h-index, considering different time windows and citation percentiles (levels of citation for considering an article as highly cited compared to others in the same year and category). The authors use four journal categories (Clarivate Analytics Web of Science) which are quite different according to the publication profiles and citation levels (Information Science & Library Science, Operations Research & Management Science, Ophthalmology, and Physics Condensed Matter).

After analyzing 20 different indicators, depending on the citation percentile and the time window in which citations are counted, the indicator that seems to best homogenize the categories is the one that considers a time window of two years and a citation level of 10 percent.

The percentage of highly cited articles in a journal is field normalized (comparable between scientific categories), independent of the journal size and also robust to the presence of articles with a high number of citations.

Flexible return policies are offered by the manufacturers to encourage the retailers announcing a lenient returns scheme to their customers.

This study considers the distribution of durable products in a supply chain where the demand is sensitive to sales effort and retail price. Using a game theoretic framework, the paper presents an assessment of the strategic effect of flexible returns policy announced by the manufacturer under retail competition and highlights its implications on profitability.

Comparative analysis of monopolistic and duopolistic competition provides a better understanding about the repercussions and related facts on offering a flexible returns policy in these environments. It is profitable for the manufacturer to offer a flexible returns policy when there is retail competition than under monopolistic condition.

Practitioners view returns policy offered as an insurance given to the buyers and they infer it to be a better mechanism for doing business. Lenient returns policy promotes the sales by increasing the trust on the retailer and boosts up the perception of quality about the product by lowering the perceived risk for customers.

Effective product return strategies such as being lenient in terms of time, money, effort, scope and exchange can result in increased revenues, lower cost and improved profitability to the manufacturer and retailer, at the same time offering an enhanced level of customer service.

Integration is a key element of supply chain management (SCM) and a lot of research has been executed within the field of supply chain integration (SCI). The purpose of this paper is to particularly identify the intellectual research front and foundation of SCI and how they developed over time.

The authors examined more than 1,700 peer-reviewed academic papers that were published between 1995 and 2019 in nearly 40 relevant peer-reviewed academic journals (all indexed in Web of Science). The authors analysed the structure of more than 55,000 individual references with the R-package bibliometrix and used VOSviewer for visualization.

The SCI research front is characterized by papers that show the effects of SCI on the firm performance, the consequences of SCI on SCM in general and present the enablers of SCI. The research front is embedded within the resource-based, transaction cost and contingency theory. The intellectual foundation refers to conceptual modelling, definitional clarification and integration dimensions. The research identifies Frohlich and Westbrook’s (2001) paper as the central reference for this research area. The dynamic evolution of the intellectual foundation of SCI changed from theorising in Phase 1 (1995–2006) towards empirical testing in Phase 2 (2007–2019).

The results refer to the SCI discussion within a preselected number of peer-reviewed academic journals and to the data quality as provided by the Web of Science.

The study explored the research front and intellectual foundation of SCI. It reveals the most important papers and journals of this area by using bibliometric tools such as bibliometrix, biblioshiny and VOSviewer. The paper shows trends in research themes, theories and methodological developments.