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Previous studies have often yielded mixed results in relation to the similar-to-me effect on extra-role behaviors. Based on social exchange theory, the purpose of this paper is to uncover the contribution of personality similarity to organizational citizenship behavior (OCB), a type of extra-role behaviors.

Questionnaire surveys were conducted in a multinational bank in Hong Kong. The participants were matched sample of 403 customer service representatives from 81 teams and their corresponding team supervisors.

Personality similarity to peers and supervisors had a positive impact on individual OCB (OCB-I) and organizational OCB (OCB-O), respectively, through better communication and social integration. Moreover, personality similarity to peers was related only to OCB-I, whereas personality similarity to supervisor was associated only with OCB-O.

Subordinates perform different facets of OCB depending on the subjects they are similar to in terms of personality. Being similar to others could facilitate communication and social integration, which in turn promote OCB targeted at similar individuals. The importance of distinguishing the similarity effects of peers and supervisors separately as well as scrutinizing the effects of different forms of OCB warrants future research attention.

Managers can promote OCB by enhancing communication and social integration among employees and supervisors.

As OCB enhances organizational effectiveness, the economic development of society in general will eventually benefit from having more effective organizations.

This study addresses the inconsistent findings of previous studies regarding the impact of similarity on OCB. It demonstrates the contribution of personality similarity to OCB beyond the confounding effects of judgment bias. It also advances theory by studying personality similarity to peers in addition to the commonly studied similarity to supervisors.

Explores the extent of employee surveillance in the western world and queries why the USA uses surveillance measures to a greater extent than other developed nations. Suggests that American managers choose surveillance methods which include the control of workers’ bodies in the production process. Lists the batteries of tests and monitoring to which US employees can now be subjected – including searching employee computer files, voice/e‐mail, monitoring telephone calls, drug tests, alcohol tests, criminal record checks, lie detector and handwriting tests. Notes also the companies which are opposed to worker and consumer privacy rights. Pinpoints the use of surveillance as a means to ensure that employees do not withold production. Reports that employees dislike monitoring and that it may adversely affect their performance and productivity. Argues that Americans like to address complex social problems with technological means, there are no data protection laws in the USA, and that these two factors, combined with the “employment‐at‐will” doctrine, have all contributed to make it possible (and easy) for employers to use technological surveillance of their workforce. Outlines some of the ways employers insist on the purification of workers’ bodies.

This paper aims to propose a risk identification method which is a synthesis of existing tools and techniques.

Risks are viewed as a temporal hierarchy of major decisions or events at the highest level, projects at the middle level, and routine operations at the lowest level. Furthermore, risks emerge as organizational activities progress over time. The organizational activities, called movements in this paper, typically follow the phases of routine (operations) > major decision/event > project > adjustment > routine which correspond to the chosen temporal hierarchy. Risks are identified by examining the movements in all applicable phases of their development. The method was applied in a case study of an enterprise in the energy sector.

Focus on movements bridges company silos. Risk logs make sense only when supplied with visualization tools. The future state of the enterprise's routines should be modelled early in the decision‐making process. Attention should be paid to changes that major decisions, events, and projects impose on organizational routines.

The method belongs to the minority of approaches which explore risk evolution, relationships, and hierarchy rather than risk likelihood and impact. Risk evolution is explored by choosing movements as the basic units of risk identification. Risk relationships are detected on the level of routines where risk relationships are the least obvious but most important. The chosen hierarchy serves an enterprise‐deep view of risks and makes it possible to be alert for periods when the organization's risks change or new ones emerge.

Looks at consumer research in Greater China including Mainland China, Hong Kong and Taiwan. Maps out the contributions within this area and guides future research. Examines the state of the art over the 1979‐97 period, with particular emphasis on the topics that have been researched, the extent of the theory development in the field and the methodologies used in conducting research. Uses content analysis to review 75 relevant articles. Suggests that, while a considerable breadth of topics have been researched, there remains much to be done, there is further room for theoretical development in Chinese consumer behaviour studies; and the methodologies used need improvement and further refinement.

In this paper, the authors investigate the impact of the confirmation bias on returns, expectations and hedging of optimistic and pessimistic traders in the cryptocurrencies, commodities and stock markets before and during COVID-19 periods.

The authors investigate the impact of the confirmation bias on the estimated returns and the expectations of optimistic and pessimistic traders by employing the financial stochastic model with confirmation bias. Indeed, the authors compute the optimal portfolio weights, the optimal hedge ratios and the hedging effectiveness.

The authors find that without confirmation bias, during the two sub periods, the expectations of optimistic and pessimistic trader’s seem to convergence toward zero. However, when confirmation bias is particularly strong, the average distance between these two expectations are farer. The authors further show that, with and without confirmation bias, the optimal weights (the optimal hedge ratios) are found to be lower (higher) for all pairs of financial market during the COVID-19 period as compared to the pre-COVID-19 period. The authors also document that the stronger the confirmation bias is, the lower the optimal weight and the higher the optimal hedge ratio. Moreover, results reveal that the values of the optimal hedge ratio for optimistic and pessimistic traders affected or not by the confirmation bias are higher during the COVID-19 period compared to the estimates for the pre-COVID period and inversely for the optimal hedge ratios and the hedging effectiveness index. Indeed, either for optimists or pessimists, the presence of confirmation bias leads to higher optimal hedge ratio, higher optimal weights and higher hedging effectiveness index.

The findings of the study provided additional evidence for investors, portfolio managers and financial analysts to exploit confirmation bias to make an optimal portfolio allocation especially during COVID-19 and non-COVID-19 periods. Moreover, the findings of this study might be useful for investors as they help them to make successful investment decision in potential hedging strategies.

First, this is the first scientific work that conducts a stochastic analysis about the impact of emotional biases on the estimated returns and the expectations of optimists and pessimists in cryptocurrency and commodity markets. Second, the originality of this study stems from the fact that the authors make a comparative analysis of hedging behavior across different markets and different periods with and without the impact of confirmation bias. Third, this paper pays attention to the impact of confirmation bias on the expectations and hedging behavior in cryptocurrencies and commodities markets in extremely stressful periods such as the recent COVID-19 pandemic.

Employees are increasingly expected to organize their own human resource development activities. To what extent and how exactly employees in various organizational contexts manage to shape their individual learning paths however remains largely unclear. The purpose of this present study is to explore, leaning on the empirical Learning-Network Theory (LNT) research and its findings, how employees in different occupations create learning paths that are attuned to their specific work context.

The paper reviews 23 MSc theses based on 14 distinct data sets collected between 2005 and 2015, containing approximately 1,484 employees from some 45 organizations and across various professions. The teachers, nurses, postal, software, telecom, railway and logistics company employees were mostly based in the Netherlands. The analysis focuses on learning-path types and learning-path strategies found in the 23 studies.

Motives, themes, activities, social contexts and facilities were found to be instrumental in explaining differences among individual learning paths. A total of 34 original learning-path types and strategies were found to cluster under 12 higher-order labels. Some of these were based on learning motive, some on learning theme, some on core learning activities, some on social learning context and a few on a combination of these elements. Overall, the socially oriented learning-path strategy was the most prevalent, as it was found among nurses, employees of software/postal/telecom, railway and logistics company employees, as well as teachers in two schools.

The paper presents the first overview of empirical studies on employee learning path(s) (strategies). In addition, it strengthens the empirical basis of the LNT.

This study aims to examine the impact of lean manufacturing (LM) on the financial performance of companies affected by emergency situations. It additionally explores the role of advanced manufacturing technologies (AMTs) in complementing LM to enhance financial performance in emergency and non-emergency situations.

Both survey and archival data were collected from 219 manufacturing companies in China. With longitudinal data collected before and after an emergency situation (i.e. Typhoon Rumbia), regression analysis was conducted to investigate the effects of LM and AMTs on financial performance in different contexts.

Our results reveal an inverted U-shaped relationship between LM and financial performance in the context of emergency. We also found that AMTs exerted a positive moderation effect on the inverted U-shaped relationship, indicating high levels of AMTs that mitigated the inefficiency of LM in coping with supply chain emergencies.

Through simultaneous investigation of LM and AMTs as bundles of practices and their fit with different contexts, this study takes a systems approach to fit that advances the application of contingency theory in the Operations Management literature to more complex patterns of fit.

This study illuminates how AMTs support LM practices in facilitating organizational performance in different contexts. Specifically, this study unravels the interaction mechanisms between AMTs and LM in influencing financial performance in emergency and non-emergency situations.

Supply chain management (SCM) proficiency is generally associated with superior business performance. Yet, SCM research continues to focus predominantly on the performance of individual firms, rather than on the collective performance of multiple supply chain participants as espoused by the extended enterprise (EE) concept. In response to calls for quantitative studies that examine the collective performance of multiple supply chain participants, this research study compares the combined performance of triads comprising focal firms recognized for their relative SCM proficiency and their upstream (supplier) and downstream (customer) supply chain partners with that of their close industry competitors' triads.

The triadic, longitudinal examination of multiple supply chain participants' collective performance utilized archival financial data of the period 2007–2017 from the Compustat database and the supply chain (SPLC) function of Bloomberg.

Findings of this study indicated that supply chain triads that included focal firms recognized for their relative SCM proficiency experienced significantly lower sales and general administrative expenses and significantly higher productivity, return on assets and profitability over time than their close industry competitors' triads. However, contrary to expectations, the performance advantages identified did not extend to revenue growth.

Supply chain triads cannot fully represent entire supply chains or EEs. However, this study’s triadic analysis can be viewed as a practically achievable proxy for further validating the EE concept. Moreover, based on assertions that triadic studies are suitable for SCM research and on empirical studies that consistently show individual firms recognized for their relative SCM proficiency outperform competitors, the authors contend that the study’s findings appropriately corroborate the value of the EE concept.

Because such empirical evidence is so rare, the consistent, collective performance advantages identified in this study should be highly significant to managers.

Robust, longitudinal evidence that supply chain triads which include focal firms recognized for relative SCM proficiency collectively outperform their close industry competitors' triads extends generally accepted associations between SCM proficiency and business performance, suggesting that the application of extended resource-based view (ERBV) in supply chain contexts warrants further examination and further substantiates the efficacy of the EE concept.