ISSN : 0368-492X
Published by: Emerald (10.1108)
Total articles ≅ 5,166
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Purpose This article proposes a strategy to make the testing step easier, generating user acceptance tests (UATs) in an automatic way from requirements artifacts. Design/methodology/approach This strategy is based on two modeling frameworks: scenarios and task/method paradigm. Scenarios are a requirement artifact used to describe business processes and requirements, and task/method paradigm is a modeling paradigm coming from the artificial intelligence field. The proposed strategy is composed of four steps. In the first step, scenarios are described through a semantic wiki website. Then scenarios are automatically translated into a task/method model (step two). In the third step, the task/method model obtained in step two is executed in order to produce and store all possible achievements of tasks and thus scenarios. The stored achievements are saved in a data structure called execution tree (ET). Finally, from this ET (step four), the UATs are generated. Findings The feasibility of this strategy is shown through a case study coming from the agriculture production systems field. Originality/value Generally, test design approaches deal with a small number of variables describing one specific situation where a decision table or workflow is used to design tests. The proposed approach can deal with many variables because the authors rely on scenarios that can be composed in order to obtain a tree with all the testing paths that can arise from their description.
Purpose This study aims to provide an overview of what characterizes the current state of research in the field of cloud computing use in human resource management (HRM) with the identification, analysis and classification of the existing literature and lines of research addressed and to provide guidance for future research. Design/methodology/approach The systematic literature review (SLR) technique has been used to identify, select, analyze and evaluate the existing publications on cloud computing and HRM. A total of 35 papers published up to December 2020 have been obtained from the Web of Science (WoS) scientific database. The research design has allowed us to determine what characterizes the current state of research on the use of cloud computing in HRM and obtain a novel classification of the literature that identifies four lines of research and the contributions in each line and has allowed us to define the future research agenda. Findings The four groups into which the papers on the cloud computing-HRM relationship have been classified are: (1) studies focused on the development of cloud platforms for HRM that highlight technical aspects, (2) papers that focus on the concept of human resource elasticity, (3) papers on the adoption and/or implantation of cloud platforms for HRM and (4) studies that highlight the effects or implications of cloud platforms for HRM. This paper proposes some new opportunities for future research and presents some helpful implications from the theoretical and management perspectives. Research limitations/implications This study uses only scientific articles in the WoS database with a Journal Citation Report (JCR) or SCImago Journal Rank (SJR) impact. Originality/value This paper provides an overview of the knowledge on cloud computing and HRM research and offers recommendations for future research.
Purpose In this paper the interconnectedness among financial institutions and the level of systemic risks of four types of Chinese financial institutions are investigated. Design/methodology/approach By the means of RAS algorithm, the interconnection among financial institutions are illustrated. Different methods, including Linear Granger, Systemic impact index (SII), vulnerability index (VI), CoVaR, and MES are used to measure the systemic risk exposures across different institutions. Findings The results illustrate that big banks are more interconnected and hold the biggest scales of inter-bank transactions in the financial network. The institutions which have larger size tend to have more connection with others. Insurance and security companies contribute more to the systemic risk where as other institutions, such as trusts, financial companies, etc. may bring about severe loss and endanger the financial system as a whole. Practical implications Since other institutions with low levels of regulation may bring about higher extreme loss and suffer the whole system, it deserves more attention by regulators considering the contagion of potential risks in the financial system. Originality/value This study builds a valuable contribution by examine the systemic risks from the perspectives of both interconnection and tail risk measures. Furthermore; Four types financial institutions are investigated in this paper.
Purpose This research aims to figure out whether the pool testing method of SARS-CoV-2 for COVID-19 is effective and the optimal sample size is in one bunch. Additionally, since the infection rate was unknown at the beginning, this research aims to propose a multiple sampling approach that enables the pool testing method to be utilized successfully. Design/methodology/approach The authors verify that the pool testing method of SARS-CoV-2 for COVID-19 is effective under the situation of the shortage of nucleic acid detection kits based on probabilistic modeling. In this method, the testing is performed on several samples of the cases together as a bunch. If the test result of the bunch is negative, then it is shown that none of the cases in the bunch has been infected with the novel coronavirus. On the contrary, if the test result of the bunch is positive, then the samples are tested one by one to confirm which cases are infected. Findings If the infection rate is extremely low, while the same number of detection kits is used, the expected number of cases that can be tested by the pool testing method is far more than that by the one-by-one testing method. The pool testing method is effective only when the infection rate is less than 0.3078. The higher the infection rate, the smaller the optimal sample size in one bunch. If N samples are tested by the pool testing method, while the sample size in one bunch is G, the number of detection kits required is in the interval (N/G, N). Originality/value This research proves that the pool testing method is not only suitable for the situation of the shortage of detection kits but also the situation of the overall or sampling detection for a large population. More importantly, it calculates the optimal sample size in one bunch corresponding to different infection rates. Additionally, a multiple sampling approach is proposed. In this approach, the whole testing process is divided into several rounds in which the sample sizes in one bunch are different. The actual infection rate is estimated gradually precisely by sampling inspection in each round.
Purpose Outsourcing remanufacturing is a major form of remanufacturing, and emission reduction is an important part of a manufacturer's production. This paper aims to investigate carbon emission reduction strategies in a closed-loop supply chain (CLSC) with outsourcing remanufacturing and design a contract to coordinate the CLSC. Design/methodology/approach The authors establish two-period game models between an original equipment manufacturer (OEM) and third-party remanufacturer (TPR) in different scenarios, including decentralized decision, centralized decision and coordinated decision. Furthermore, the authors study the optimal decisions by maximizing the profit model. The authors also investigate the impact of a carbon tax and emission reduction on the optimal decisions through comparative analysis. Findings Emission reduction increases the quantity of new products and the OEM's profit. However, emission reduction decreases the outsourcing fee, which is not conducive to remanufacturing; thus, the TPR's profit does not necessarily increase. Compared with a decentralized scenario, the output of remanufactured products and the total profit increase. When the acceptance level of remanufactured products is high enough or when emissions from remanufacturing are low enough, the total carbon emissions are reduced in the centralized scenario. For the coordination of the CLSC, the OEM needs to increase the outsourcing fee and the TPR needs to share part of the emission reduction costs. Research limitations/implications The TPR can choose three different remanufacturing strategies, namely, no remanufacturing, partial remanufacturing or full remanufacturing. For the majority of firms, it is difficult to remanufacture all used products. Therefore, the analysis is based only on partial remanufacturing. Practical implications The results provide insights for remanufacturing and emission reduction decisions, as well as a decision basis for the cooperation between the OEM and TPR. Originality/value The authors combine the OEM's carbon emission reduction with outsourcing remanufacturing, and investigate the impact of technological spillover on the TPR's profit.
Purpose Given the huge investment and complexity of information technology, it is imperative that boards of directors fully play their important role in promoting firms' IT success. This study aims to investigate the effects of boards of directors' external ties on firms' IT success from the perspective of resource dependence theory. Design/methodology/approach According to the method of the matched sample comparison group, a total of 576 samples of listed enterprises in three periods were obtained. Findings Results show that both boards' political ties and boards' business ties have a positive impact on firms' IT success. Environmental uncertainty and the institutional environment play different roles in the relationships between two types of external ties and firms' IT success. Specifically, the results show that the institutional environment can regulate the influence of the political association of directors on firms' IT success negatively. In addition, environmental uncertainty regulates the influence of directors' political association on firms' IT success negatively, as well as the influence of directors' commercial association with firms' IT success. Research limitations/implications The external ties were measured by cross-sectional data. And the current study focused on two fundamental types of external ties. Originality/value Boards' external ties are studied from both political and business perspectives, and the effects of these two types of external ties on firms' IT success are compared. Additionally, the moderating effects of the institutional environment (macro level) and environmental uncertainty (micro level) in these relationships are investigated.
Purpose One of the main advantages of the proposed model is that it is flexible to generate n-day pairings simultaneously. It means that, despite previous researches, one-day to n-day pairings can be generated in a single model. The flexibility in generating parings causes that the proposed model leads to better solutions compared to existing models. Another advantage of the model is minimizing the risk of COVID-19 by limitation of daily flights as well as elapsed time minimization. As airports are among high risk places in COVID-19 pandemic, minimization of infection risk is considered in this model for the first time. Genetic algorithm is used as the solution approach, and its efficiency is compared to GAMS in small and medium-size problems. Design/methodology/approach One of the most complex issues in airlines is crew scheduling problem which is divided into two subproblems: crew pairing problem (CPP) and crew rostering problem (CRP). Generating crew pairings is a tremendous and exhausting task as millions of pairings may be generated for an airline. Moreover, crew cost has the largest share in total cost of airlines after fuel cost. As a result, crew scheduling with the aim of cost minimization is one of the most important issues in airlines. In this paper, a new bi-objective mixed integer programming model is proposed to generate pairings in such a way that deadhead cost, crew cost and the risk of COVID-19 are minimized. Findings The proposed model is applied for domestic flights of Iran Air airline. The results of the study indicate that genetic algorithm solutions have only 0.414 and 0.380 gap on average to optimum values of the first and the second objective functions, respectively. Due to the flexibility of the proposed model, it improves solutions resulted from existing models with fixed-duty pairings. Crew cost is decreased by 12.82, 24.72, 4.05 and 14.86% compared to one-duty to four-duty models. In detail, crew salary is improved by 12.85, 24.64, 4.07 and 14.91% and deadhead cost is decreased by 11.87, 26.98, 3.27, and 13.35% compared to one-duty to four-duty models, respectively. Originality/value The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.
Purpose Drawing on the stress and coping theory, conservation of resources (COR) theory and social role theory, this study aims to investigate the impact of social media overload on knowledge withholding behavior and examine the gender differences in social media overload, engendering knowledge withholding. Design/methodology/approach By hiring a professional online survey company, this study collected valid responses from 325 general social media users. The structural equation modeling (SEM) technique, bootstrapping method and multi-group analysis were used to test the proposed theoretical model. Findings The empirical results reveal that three types of social media overload positively affect users' knowledge withholding behavior and that emotional exhaustion significantly mediates the above relationships. The multi-group analysis demonstrates that gender differences do exist in the decision-making process of knowledge withholding; for example, females are more likely than males to become emotionally exhausted from social media overload, while males are more likely than females to engage in knowledge withholding behavior in the case of emotional exhaustion. Originality/value This study contributes to the existing body of knowledge by examining the relationship between social media overload and knowledge withholding, verifying the mediating role of emotional exhaustion as the key mechanism linking them, and narrowing the research gap of lacking gender differences research in knowledge withholding literature.
Purpose This study utilized “social cognitive theory” to compare the impacts of organizational members' hedonic and work-related use of public social networks (SNs) and enterprise social networks (ESNs) on job satisfaction. Design/methodology/approach The participants comprised 240 employees who were able to simultaneously use SNs and ESNs in the workplace with regard to both hedonic and work-related motives. The measurement and structural models were evaluated using partial least squares structural equations modeling (PLS-SEM). Findings The results show that organizational members' hedonic and work-related use of public SNs enhances job satisfaction. However, the hedonic and work-related use of ESNs has negative and positive impacts on job satisfaction respectively. Originality/value The main theoretical contribution of this study lies in showing that employees' use of social networks does not necessarily entail detrimental or beneficial consequences and depending on different factors the outcomes are different. Following a comprehensive review of the literature, users' incentives and platforms emerged as two different factors contributing to the outcomes arising from the use of social networks in the workplace. Although a few studies have explored the impacts of organizational members' use of social networks on job satisfaction, none have done so in relation to different user incentives and platforms.
Purpose The presence of asymmetric information exists between firms and the government about the firms' green innovation; this may lead to the firm's moral hazard problem of misusing the government subsidy on the green innovation. Such a problem is not fully considered by the existing literature. The purpose of this study is to explore how government subsidy affects green innovation when the information of firms' innovation cannot be completed observed, and figure out the mechanisms that can alleviate the negative impact of information asymmetry, which helps to explain the factors that motivate the firms to actively engage into the green innovation with the government subsidy. Design/methodology/approach In a theoretical model under imperfect information in which the firm's activity on green innovation may not be fully observed, the firm could be either altruistic or not; an altruistic firm has stronger incentive to engage into corporate social responsibility (CSR) activities such as green innovation. With the presence of asymmetric information, the authors analyze the possibility of a firm's moral hazard and try to find out the condition on the information quality that can avoid such problem. To examine the results of theoretical analysis, the authors use the data of Chinese listed companies in a corresponding empirical analysis. On the basis of both theoretical and empirical the authors try to figure out the effect of the government subsidy on the green innovation by enterprise and the role of firm's characteristics of social responsibility and information quality in the green innovation with the government subsidy. Findings The results show that the government subsidy can promote the firm's green innovation, especially for those that are more socially responsible. The asymmetric information, however, leads to inefficiency on the green innovation. This is because that the low-quality information about the firm's behavior raises the possibility of a moral hazard. Moreover, the analyst coverage could be an efficient way to improve the quality of information, alleviating the moral hazard problem of the firm's green innovation. The main contribution is to fill the gap in the study of the government subsidy on green innovation under asymmetric information and to provide the mechanism to improve the efficiency of the subsidy to motivate green innovation by enterprise. Practical implications A crucial implication to policymakers is to complete and improve the system of information in the market, which can form an efficient incentive compatibility between the enterprises and the public. Such incentive compatibility can attract the enterprises to better use the government subsidy into green innovation and receive a long-run return from the public's positive feedback for their contribution on the social good. Originality/value Existing studies are concerned about antecedents of green innovation do not completely focus on the relationship between government subsidy and green innovation. The present paper considers that information asymmetry between the government and firms may affect the impact of government subsidy on the firms' green innovation. This conjecture is studied by the theoretical model and verified by an empirical analysis using the data of Chinese listed companies. Additionally, the empirical analysis explores the moderating effect of CSR characteristics of firms, and the analyst coverage can positively affect the promotion of the government subsidy on the firms' green innovation.