Multi-stage semi-open queuing networks (SOQNs) are widely used to analyze the performance of multi-stage manufacturing systems and automated warehousing systems. While there are several methods available for solving single-stage SOQNs, solution methods for multi-stage SOQNs are limited. Decomposition of a multi-stage SOQN into single-stage SOQNs and evaluation of an individual single-stage SOQN is a possibility. However, the challenge lies in obtaining the job departure process information from an upstream single-stage SOQN to evaluate the performance of a downstream single-stage SOQN. In this paper, we propose a two-moment approximation approach for estimating the squared coefficient of variation of the job inter-departure time from a single-stage SOQN, which can serve as an input to link multi-stage SOQNs. Using numerical experiments, we test the robustness of the proposed approach for various input parameter settings for both single and multi-class jobs. We find that the proposed approach works quite well, particularly when the coefficient of variation of the job inter-arrival time is less than two. We demonstrate the efficacy of the proposed approach using a case study on a multi-tier shuttle-based compact storage system and benchmark our results with an existing approach. The results indicate that our approach yields more accurate estimates of the performance measures in comparison to the existing approach in the literature. © 2020 Elsevier Ltd

Operations research (OR) has been at the core of decision making since World War II, and today, business interactions on different platforms have changed business dynamics, introducing a high degree of uncertainty. To have a sustainable vision of their business, firms need to have a suitable decision-making process at each stage, including minute details. Our study reviews and investigates the existing research in the field of decision support systems (DSSs) and how artificial intelligence (AI) capabilities have been integrated into OR. The findings of our review show how AI has contributed to decision making in the operations research field. This review presents synergies, differences, and overlaps in AI, DSSs, and OR. Furthermore, a clarification of the literature based on the approaches adopted to develop the DSS is presented along with the underlying theories. The classification has been primarily divided into two categories, i.e. theory building and application-based approaches, along with taxonomies based on the AI, DSS, and OR areas. In this review, past studies were calibrated according to prognostic capability, exploitation of large data sets, number of factors considered, development of learning capability, and validation in the decision-making framework. This paper presents gaps and future research opportunities concerning prediction and learning, decision making and optimization in view of intelligent decision making in today’s era of uncertainty. The theoretical and managerial implications are set forth in the discussion section justifying the research questions. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.

Presence of excess zero in ordinal data is pervasive in areas like medical and social sciences. Unfortunately, analysis of such kind of data has so far hardly been looked into, perhaps for the reason that the underlying model that fits such data, is not a generalized linear model. Obviously some methodological developments and intensive computations are required. The current investigation is concerned with the selection of variables in such models. In many occasions where the number of predictors is quite large and some of them are not useful, the maximum likelihood approach is not the automatic choice. As, apart from the messy calculations involved, this approach fails to provide efficient estimates of the underlying parameters. The proposed penalized approach includes ?1 penalty (LASSO) and the mixture of ?1 and ?2 penalties (elastic net). We propose a coordinate descent algorithm to fit a wide class of ordinal regression models and select useful variables appearing in both the ordinal regression and the logistic regression based mixing component. A rigorous discussion on the selection of predictors has been made through a simulation study. The proposed method is illustrated by analyzing the severity of driver injury from Michigan upper peninsula road accidents. © 2020 The Authors. Statistica Neerlandica © 2020 VVS.

Many intra-logistics systems, such as automated container terminals, distribution warehouses, and cross-docks, observe parallel process flows, which involve simultaneous (parallel) operations of independent resources while processing a job. When independent resources work simultaneously to process a common job, the effective service requirement of the job is difficult to estimate. For modeling simplicity, researchers tend to assume sequential operations of the resources. In this paper, we propose an efficient modeling approach for parallel process flows using two-phase servers. We develop a closed queuing network model to estimate system performance measures. Existing solution methods can evaluate the performance of closed queuing networks that consist of two-phase servers with exponential service times only. To solve closed queuing networks with general two-phase servers, we propose new solution methods: an approximate mean value analysis and a network aggregation dis-aggregation approach. We derive insights on the accuracy of the solution methods from numerical experiments. Although both solution methods are quite accurate in estimating performance measures, the network aggregation dis-aggregation approach consistently performs best. We illustrate the proposed modeling approach for two intra-logistic systems: a container terminal with automated guided vehicles and a shuttle-based compact storage system. Results show that approximating the simultaneous operations as sequential operations underestimates the container terminal throughput on average by 28% and at maximum up to 47%. Similarly, considering sequential operations of the resources in the compact storage system results in an underestimation of the throughput capacity up to 9%. © 2020 Elsevier B.V.

Measuring publication success of a researcher is a complicated task as publications are often co-authored by multiple authors, and so, it requires comparison of solo publications with joint publications. In this paper, like Price (1981), we argue for an egalitarian perspective in accomplishing this task. More specifically, we justify the need for an ethical perspective in quantifying academic author by identifying certain ethical difficulties of some popular contemporary indices used for this purpose. And then we show that for any given dataset of research papers, the unique method satisfying the ethical notions of identity independence and performance invariance must be the egaliatarian E-index proposed by Bose, Pal, and Sappington (2010) and Price (1981). In our setting, this egalitarian method divides authorship of joint projects equally among authors and sums across all publications of each author. © 2019 John Wiley & Sons, Ltd.

Climate change is a key societal and economic challenge. Despite widespread recognition for the need for urgent action on climate change, transformation to a zero carbon economy is still elusive. While there are detailed accounts of organisational responses to climate change impacts, little is known about climate change inaction. We adopt the theoretical framework of resilience in social-ecological systems to explore the change processes needed to overcome climate change inaction. Through an in-depth case study of an Australian energy company, we identify the impediments to climate change action due to rigidity and scarcity traps at three levels: micro (organisation), meso (industry), and macro (government). These traps inhibit transformation from a fossil fuel regime to a renewable energy regime. Our study contributes to a multi-level theory of organisational inaction on climate change by identifying specific causal factors that erode systemic adaptive capacity, increasing the probability of rigidity and scarcity traps. We find that different inaction occurs at all three levels, and is closely interconnected (across levels) within a social-ecological system, due to dynamic antecedents (e.g. changing individual attitudes, business practices, and government policies). Competencies, resources, and cultural changes can help organisations traverse rigidity and scarcity traps to overcome climate change inaction. © 2020, © 2020 Environment Institute of Australia and New Zealand Inc.

New container terminals are embracing robotized transport vehicles such as lift-automated guided vehicles (LAGVs) and automated guided vehicles (AGVs) to enhance the terminal throughput capacity. Although LAGVs have a high container handling time, they require less coordination with other terminal equipment in comparison with AGVs. In contrast, AGVs are hard-coupled resources, require less container handling times, but operate with high coordination delays in comparison with LAGVs. The effect of such operational trade-offs on terminal performance under various design parameter settings, such as yard block layout and a number of resources, is not well understood and needs to be evaluated at the terminal design phase. To analyze these trade-offs, we develop stylized semi-open queuing network models, which consist of two-phase servers and finite capacity queues. We develop a novel network decomposition method for solving the proposed queuing models. The accuracy of the solution method is validated using detailed simulation models. Using the analytical models, we study the performance trade-offs between the transport vehicle choices: LAGVs and AGVs. Our results show that the throughput capacity of the terminal in the container unloading process increases by up to 16% if LAGVs are chosen as transport vehicles instead of AGVs. However, at certain parameter settings, specifically, when the arrival rate of containers is low, the throughput time performance of the terminal is higher (up to 8%) with AGVs than with LAGVs. We also derive insights on the yard block layout and the technology choice for quay cranes. © Copyright © 2020 “IISE”.

A series of tailor made experiments were executed on a representative Indian household sample to investigate the influence of risky and ambiguous options on the choices made by the subjects. The objective of the study was to understand the impact of prior results on subsequent decisions made along with identifying role of demographic factors impacting their choices. The experiment showed that subjects displayed an escalation of commitment while playing the game in domains of losses. The results show that attitude of ambiguity aversion cannot be generalized in totality and role of cultural factors needs to be explored further. © 2019 Elsevier B.V.

In this article, interval-censored competing risks data are analyzed when some of the causes of failure are missing. The vertical modeling approach has been proposed here. This approach utilizes the data to extract information to the maximum possible extent especially when some causes of failure are missing. The maximum likelihood estimates of the model parameters are obtained. The asymptotic confidence intervals for the model parameters are constructed using approaches based on observed Fisher information matrix, and parametric bootstrap. A simulation study is considered in detail to assess the performance of the point and interval estimators. It is observed that the proposed analysis performs better than the complete case analysis. This establishes the fact that the our methodology is an extremely useful technique for interval-censored competing risks data when some of the causes of failure are missing. Such analysis seems to be quite useful for smaller sample sizes where complete case analysis may have a significant impact on the inferential procedures. Through Monte Carlo simulations, the effect of a possible model misspecification is also assessed on the basis of the cumulative incidence function. For illustration purposes, three datasets are analyzed and in all cases the conclusion appears to be quite realistic. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

Leadership and knowledge are often paired together. Yet, certain forces that operate on businesses and individuals are often unknowable. In this study, we consider leaders’ perceptions of the consequences of not knowing and how leaders discursively cope with a sense of not knowing. Based on interviews with 33 participants working in multinational companies in India, we find that leaders perceive negative consequences of not knowing and engage in discursive tactics such as posing, delaying, clarifying, admitting, being silent, and stating “I don’t know,” that sustain and are sustained by the Discourse of leadership as knowledge. The findings contribute to the discursive leadership literature by demonstrating tactics leaders use as they attempt to balance the discursive construction of leadership as knowledge and lived experiences of not knowing. We discuss how the Discourse of leadership as knowledge will hamper knowledge extension as it undermines not knowing and privileges knowing over not knowing. © The Author(s) 2020.

China has greatly increased the number of published works indexed in the Web of Science since 1980. This corpus of scholarship allows analysis of the creativity or innovation of that contribution, where creativity is indicated by deep conventionality and high novelty. A test is applied to analyze reference pairs in articles to search for unexpected referencing combinations at the journal–journal level. The method has shown that atypical reference pairs occur in more highly cited articles. Using articles with at least one Chinese address as indexed in Web of Science for the publication year 2007, we tagged articles based on the conventionality and novelty of the reference pairs, seeking, in particular, those articles that reveal atypicality. This atypical set of articles represented 8% of all Chinese articles, compared to the world level of 7% in 2005. China’s atypical work is also more highly cited than a similar set of records at the world level for the years 1980–2000. The findings suggest that China has advanced in its goals of establishing itself as a full participant in global science and technology. © 2020, Akadémiai Kiadó, Budapest, Hungary.

We consider convergence to Walrasian equilibrium in a situation where firms know only market price and their own cost function. We term this a situation of minimal information. We model the problem as a large population game of Cournot competition. The Nash equilibrium of this model is identical to the Walrasian equilibrium. We apply the best response (BR) dynamic as our main evolutionary model. This dynamic can be applied under minimal information as firms need to know only the market price and the their own cost to compute payoffs. We show that the BR dynamic converges globally to Nash equilibrium in an aggregative game like the Cournot model. Hence, it converges globally to the Walrasian equilibrium under minimal information. We extend the result to some other evolutionary dynamics using the method of potential games. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

This paper analyses a model of coordination in a supply chain consisting of two manufacturers, two products, and a single retailer under full information. Market demand for each of the manufacturer's products allows for both price and cross-price elasticities. We consider a Stackelberg game between the retailer and the two manufacturers and solve for the subgame perfect equilibrium wholesale price chosen by each of the manufacturers, the retail price charged by the retailer for each of two products, as well as the equilibrium demands for the two products. Unlike a classical dyadic supply chain, we show that only under certain allocations of the total profit between the manufacturers and the retailer is it the case that the vertically integrated chain is the preferred supply chain structure, even though it provides the highest total profit. An important result is that vertical integration is less advantageous when products are closer substitutes. We also show that a revenue sharing contract can coordinate this chain, but only when the manufacturers set their wholesale prices below their marginal costs of production. Finally, we show that the retailer can choose to integrate partially with one manufacturer to achieve a Pareto improving profit outcome. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

The coronavirus pandemic is having a clear impact on the supply chains of virtually all manufacturers, retailers, and wholesalers. As the world attempts to navigate through this difficult time, most companies are struggling to maintain a steady flow of required goods and services. Whether it is frozen foods and grocery items (i.e., toilet papers), or ventilators and masks, or even the services (i.e., clinic visits), the supply chain has been facing multiple obstacles. Most models and frameworks built in the extant literature are not been able to capture these disruptions and as such, firms are not having proper strategies to deal with. For firms with complex supply chains (i.e., manufacturing, retailing), it is indeed critical to identify strategies to deal with such a crisis. In this paper, we intend to offer strategic insights in terms of major issues firms are facing and strategic options firms are contemplating. We rely on the twitter data from NASDAQ 100 firms to generate themes regarding the issues faced by the firms and the strategies they are adopting using text analytics tools. We find that firms are facing challenges in terms of demand-supply mismatch, technology, and development of a resilient supply chain. Moreover, moving beyond profitability, firms are experiencing difficulties to construct a sustainable supply chain. We provide futuristic strategic recommendations for the rebuilding of the supply chain. © 2020 Elsevier Inc.

Learning outcomes: The main objective of this marketing strategy case is to understand why and how a firm should evaluate and rework its own business to stay competitive and aligned with external market forces. Case overview/synopsis: Technical Solutions Group (TSG), was the India-based technical support division of Quatrro Global Services and focused on providing support to customers of large Original Equipment Manufacturers (OEMs) and software developers around the globe. Because of the increased competition and structural changes at the customer end, the business was facing flattened revenue growth and a drop in margins. TSG had to make strategic decisions on how to continue the business, either within the current paradigm of being a business to business business or transforming into a business to consumer business leveraging digital technology. Complexity academic level: This case can be used in an undergraduate (upper level) or graduate-level course on marketing strategy, digital strategy or strategic management. Supplementary materials: Teaching Notes are available for educators only. Subject code: CSS 11: Strategy. © 2020, Emerald Publishing Limited.

Purpose: The purpose of this paper is to examine the relationship between justice perceptions (distributive, procedural and interactional) and workplace bullying and to test the mediating role of psychological contract violation (PCV) in this relationship and the extent to which the mediation is moderated by power distance orientation (PDO). Design/methodology/approach: The study draws upon quantitative data collected via self-reported survey questionnaires from 422 full-time Indian managerial employees working across different service sector–based Indian organizations. Findings: The results revealed that justice perceptions (distributive, procedural and interactional) negatively correlated with workplace bullying. The hypothesized moderated mediation condition was supported as the results suggest that the PCV mediated the justice-bullying relationship and the PDO moderated this mediating pathway, i.e. indirect effects of justice (procedural and interactional) perceptions on workplace bullying via PCV were weaker for employees with a high PDO. Research limitations/implications: A cross-sectional design and the use of self-reported questionnaire data in the sample are few limitations of the study. Practical implications: This study contributes toward a better understanding of the relationships between justice, PCV and workplace bullying. It also highlights the role played by individual cultural dispositions in influencing their perceptions of workplace bullying. Given the perceptual and subjective elements of workplace bullying, understanding how justice and workplace bullying are related in not only important theoretically but also critical from a practical standpoint. Originality/value: To the best of authors' knowledge, this is the first study that links justice, PCV, workplace bullying and PDO in one study. This study is also important in terms of its context. © 2020, Emerald Publishing Limited.

Organisations invest in human capital to achieve favourable organisational performance. The purpose of this research is to explain how organisational human capital investments influence an individual’s human capital and innovative work behaviour (IWB). Drawing on Social Exchange Theory and its subset Affect Theory of Social Exchange, this study empirically examines how the human resource management activity of human capital investments manifests at the individual level by developing and testing a moderated serial mediation model. A total of 115 employees working in a diverse set of industries, such as service, manufacturing, information technology, consultancy and education, who had received at least one training from their current employer, participated in the survey. The participants completed five standardized, valid and reliable instruments. SPSS was employed for data analysis. Hypotheses were tested using regression analysis. Results show that both gratitude and knowledge management mediate the relationship between human capital and IWB and the moderating effects of job characteristics. This study extends current literature and integrates macro–micro human capital by exploring how and when human capital leads to the generation of micro social orders. The concept of micro social orders refers to repeated interactions (exchange frequency), emotional reactions, perceptions of cohesion and affective sentiments of a group/organisation due to social structures. This research also highlights how managers can establish positive reciprocity obligations and enhance employees’ gratitude that helps to achieve IWB. © 2020 Sage Publications India Pvt. Ltd.

Purpose: The purpose of this paper is to examine the interrelation between two important dimensions of gender segregation: education and occupation. It further investigates the gender wage gap. Design/methodology/approach: The author uses a three-way additive decomposition of the mutual information index – an index based on the concept of entropy. A non-parametric wage decomposition method that uses matching comparisons is used for measuring the wage gap. Findings: The results show that the extent of gender segregation in India is higher in urban areas than that in rural areas. Most of the observed segregation in rural labour markets originates from educational outcomes, whereas in urban markets it is due to occupational profile of individuals. The findings of the wage decomposition analysis suggest that education in rural areas also explains a sizeable part of the gender wage differential. Nevertheless, a large share of the wage gap remains unexplained in both rural and urban areas. Originality/value: While much research has looked at occupational segregation, less attention has been paid to educational segregation. The paper uses a unique approach to understand the joint effect of occupation and education in explaining gender segregation. © 2020, Emerald Publishing Limited.

Purpose: The purpose of this paper is to explore the under-researched dynamics of gender, workplace support, and perceived job demands in two different contexts, the United States and India. Design/methodology/approach: The paper draws from two studies conducted in different contexts (the United States and India) via different methodological approaches (quantitative and qualitative, respectively). In Study I of this paper, data was collected using questionnaires from a nationally representative sample of adult workers in the United States. In Study II, interviews were conducted with 48 workers in India, selected using convenience sampling. Findings: It was found that both in the United States and India, women perceived considerably greater job demands than men. In terms of workplace support, both the studies found that workplace culture and supervisors’ support influenced the perception of job demands, but the same was not true for coworkers’ support, which mainly helped in coping rather than actually reducing the perception of job demands. Research implications: The article contributes to research by concluding that job demands as a construct are not clearly segregated from gender demands or expectations, especially in the way women “perceive” it. Women construct job demands as “job-family” demands and workplace support as “job-family” support. Moreover, being a woman in the workplace, women feel the “burden” of gender. Practical implications: It would be useful for organizations and policy makers to understand that women remain “conscious” of their gender in the workplace, and for them, the meaning of job demands and workplace support are “job-family” demands and “work-family” support, respectively. Social implications: This research intends to contribute toward thinking about gender relations and empowerment of people within organizational and work settings from a new light. Originality/value: The present study provides an alternative way of thinking about gender, job demands, and workplace support. Its value underlies in the way it raises the voices of women workers. © 2020, Emerald Publishing Limited.

Building on transaction cost economics theory and social network theory, we investigate the impact of dimensions of buyer-supplier network (BSN) complexity (horizontal, vertical, and spatial) on firms' environmental performance, specifically, greenhouse gas (GHG) emissions. Using secondary data from diverse sources on the supply networks of 319 firms, extending to the Tier-2 level, we present and test a robust empirical model that also accounts for potential endogeneity effects. To understand this key relationship between BSN complexity and environmental performance at a deeper level, we further test the moderating influence of BSN members' reach on this key relationship. We also test the moderating effects of a focal firm's control over its BSN on this key relationship. We find that both the vertical complexity dimension and the horizontal complexity dimension of BSNs had a U-shaped relationship with the participating firms' GHG emissions. In contrast, the spatial complexity dimension of BSNs had a positive impact on the participating firms' GHG emissions. With respect to the moderating effects, we found that firms' control over their BSN negatively influenced these relationships, whereas the reach of the BSN members positively influenced these relationships. Taken together, this set of mixed-pattern findings casts new light on the broad literature of multitier BSNs, environmental sustainability, and the effective management of supply chains. The managerial implications of our findings are also discussed. © 2020 Elsevier B.V.