Essential Micro‐foundations for Contemporary Business Operations: Top Management Tangible Competencies,Relationship‐based Business Networks and Environmental Sustainability

Although various studies have emphasized linkages between firm competencies, networks and sustainability at organizational level, the links between top management tangible competencies (TMTCs) (e.g. contemporary relevant quantitative‐focused education such as big data analytics and data‐driven applications linked with the internet of things, relevant experience and analytical business applications), relationship‐based business networks (RBNs) and environmental sustainability have not been well established at micro‐level, and there is a literature gap in terms of investigating these relationships. This study examines these links based on the unique data collected from 175 top management representatives (chief executive officers and managing directors) working in food import and export firms headquartered in the UK and New Zealand. Our results from structural equation modelling indicate that TMTCs are the key determinants for building RBNs, mediating the correlation between TMTCs and environmental sustainability. Directly, the competencies also play a vital role towards environmental practices. The findings further depict that relationship‐oriented firms perform better compared to those which focus less on such networks. Consequently, our findings provide a deeper understanding of the micro‐foundations of environmental sustainability based on TMTCs rooted in the resource‐based view and RBNs entrenched in social network theory. We discuss the theoretical and practical implications of our findings, and we provide suggestions for future research.     

A three-state continuous time Markov chain model for HIV disease burden

Plasma HIV viral load (VL) is the clinical indicator used to evaluate disease burden for HIV-infected patients. We developed a covariate-adjusted, three-state, homogenous continuous time Markov chain model for HIV/AIDS disease burden among subgroups. We defined Detectable and Undetectable HIV VL levels as two transient states and Death as the third absorbing state. We implemented the exact maximum likelihood method to estimate the parameters with related asymptotic distribution to conduct hypothesis testing. We evaluated the proposed model using HIV-infected individuals from South Carolina (SC) HIV surveillance data. Using the developed model, we estimated and compared the transition hazards, transition probabilities, and the state-specific duration for HIV-infected individuals. We examined gender, race/ethnicity, age, CD4 count, place of residence, and antiretroviral treatment regimen prescribed at the beginning of the study period. We found that patients with a higher CD4 count, increased age, heterosexual orientation, white, and single tablet regimen users were associated with reduced risk of transitioning to a Detectable VL from an Undetectable VL, whereas shorter time since diagnosis, being male, and injection drug use increased the risk of the same transition.     

Big Data‐Savvy Teams’ Skills,Big Data‐Driven Actions and Business Performance

Prior studies on big data analytics have emphasized the importance of specific big data skills and capabilities for organizational success; however, they have largely neglected to investigate the use of cross‐functional teams’ skills and links to the role played by relevant data‐driven actions and business performance. Drawing on the resource‐based view (RBV) of the firm and on unique data collected from 240 big data experts working in global agrifood networks, we examine the links between the use of big data‐savvy (BDS) teams’ skills, big data‐driven (BDD) actions and business performance. BDS teams depend on multi‐disciplinary skills (e.g. computing, mathematics, statistics, machine learning and business domain knowledge) that help them turn their traditional business operations into modern data‐driven insights (e.g. knowing real‐time price changes and customer preferences), leading to BDD actions that enhance business performance. Our results, raised from structural equation modelling, indicate that BDS teams’ skills that produce valuable insights are the key determinants for BDD actions, which ultimately contribute to business performance. We further demonstrate that those organizations that emphasize BDD actions perform better compared to those that do not focus on such applications and relevant insights.     

The Application of Neural Networks and a Qualitative Response Model to the Auditor's Going Concern Uncertainty Decision*

An auditor gives a going concern uncertainty opinion when the client company is at risk of failure or exhibits other signs of distress that threaten its ability to continue as a going concern. The decision to issue a going concern opinion is an unstructured task that requires the use of the auditor's judgment. In cases where judgment is required, the auditor may benefit from the use of statistical analysis or other forms of decision models to support the final decision. This study uses the generalized reduced gradient (GRG2) optimizer for neural network learning, a backpropagation neural network, and a logit model to predict which firms would receive audit reports reflecting a going concern uncertainty modification. The GRG2 optimizer has previously been used as a more efficient optimizer for solving business problems. The neural network model formulated using GRG2 has the highest prediction accuracy of 95 percent. It performs best when tested with a small number of variables on a group of data sets, each containing 70 observations. While the logit procedure fails to converge when using our eight variable model, the GRG2 based neural network analysis provides consistent results using either eight or four variable models. The GRG2 based neural network is proposed as a robust alternative model for auditors to support their assessment of going concern uncertainty affecting the client company.     

A Robust Multivariate Procedure for the Identification of Problem Savings and Loan Institutions*

The 1980s have seen a great increase in the number of failed savings and loan institutions. In order to prevent such failures, it would be helpful if regulators have an early warning model. Such a model should be able to flag potential failed firms to prevent failure. In this paper, a robust multivariate procedure is used to successfully identify potentially failed firms well ahead of an actual failure date.     

Equi-information robust designs: Which designs are possible?

The effects of missing observations in a designed experiment are reviewed. Conditions are determined for a design to retain equal information, i.e. the same generalized variance of unknown parameters, when either any single or any pair of observations is lost. Some examples of designs with this property are given. Although there are many designs which retain equal information for the loss of exactly t observations, where t = 1,2,3,…, it is shown that it is not possible to obtain any design which retains equal information when any one and any two and also any three observations are missing.     

Exploring the effects of workplace support on work-life experience: a study of Malaysia

To date most studies of workplace support and work-life experience have been of contexts where government policies and legislation to protect employee work-life balance interests are well established, such as US, UK, and other European countries. Little scrutiny has been given to these issues in less developed economies, where support and protection in terms of work-life policies and legislation at the national level is rather limited. Malaysia, the setting of this study, provides such a context. Two types of organizational support, work flexibility and superior support, are studied for their impact on work-life experience of Malaysians. The findings of this study are based on a national survey of working adults in Malaysia. Work-life experience is conceptualized to capture conflict and enrichment aspects, as well as bidirectional effects between work and nonwork. Results show that work flexibility and superior support lower work-life conflict marginally but facilitate greater work-life enrichment among Malaysians. The paper also draws out implications of these findings for human resource development professionals operating in workplace settings within national contexts with limited mandatory work-life provisions.     

Lead time adjustment through scrap management

In a discrete parts manufacturing environment, it is necessary to compensate for the decreasing planned batch size resulting from production of scrap (defectives) in the production line, by increasing the planned production volume. This calls for a revision in the initially computed manufacturing lead time (MLT). A survey of the literature reveals that although issues related to product quantity regeneration have been studied in detail, little has been done to assess the impact on manufacturing lead times. This paper discusses the impact of scrap on manufacturing lead time in a shop with an intermittent-flow, bath-oriented, discrete-parts manufacturing environment, producing make-to-stock items.