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

In this paper, we study the hub location problem of an entrant airline that tries to maximize its share in a market with already existing competing players. The problem is modeled as a non-linear integer program, which is intractable for off-the-shelf commercial solvers, like CPLEX and Gurobi, etc. Hence, we propose four alternate approaches to solve the problem. The first among them uses the Kelley's cutting plane method, the second is based on a mixed integer second order conic program reformulation, the third uses the Kelley's cutting plane method within Lagrangian relaxation, while the fourth uses second order conic program within Lagrangian relaxation. On the basis of extensive numerical tests on well-known datasets (CAB and AP), we conclude that the Kelley's cutting plane within Lagrangian relaxation is computationally the best. It is able to solve all the problem instances of upto 50 nodes within 1% optimality gap in less than 10 minutes of CPU time. © 2020 Elsevier B.V.

The content generation strategy of a sports franchise determines whether the user engagement increases or decreases on social media platforms. Thus, the role of Chief Operating Officer (COO) is profound who generally decides and governs social media policies of the franchises. We show that the cultural differences between local-COO vis-à-vis foreign-COO-governed sports franchises reflect in their content generation strategy and are also associated with user engagement. We use Hofstede's cultural dimensions theory and extract relevant features from the tweets. Overall, the results show that user engagement is more when the content generation strategy is in alignment with fans’ national culture. The first contribution of our work is towards showing the incremental impact of power distance, individualism and collectivism on user engagement. The second contribution of our work is towards feature construction, feature selection and building authorship attribution classifiers to understand the content generation strategy. Prior literature shows that national culture impacts writing of online reviews. We investigate the role of national culture in social media content generation and user engagement and extend the literature. Our study is useful for organizations to understand the role of national culture in content generation and how it is related to user engagement. © 2020 Elsevier Ltd

The present study extends research on the role of celebrity endorsements in destination marketing by exploring various facets of the effect of celebrity endorsements in destination marketing on the consumer. More specifically, theories of source credibility, congruence, social identity and consumer cosmopolitanism, are used to build research questions that investigate the relative effectiveness of a celebrity endorsed tourism advertisement vis a vis a generic advertisement and the boundary conditions governing the same such as destination type (local/global), celebrity country of origin and consumer level factors. The research questions are addressed using four experimental studies in sequence. The same four experiments are run in three countries with different socio-cultural backgrounds to enhance generalization, with a combined sample size of 1073 respondents. Major findings suggest that a celebrity endorser is effective for a destination advertisement. Significant cross-country differences were observed in consumer affect depending on the choice of celebrity (local or global) and the destination type (i.e., domestic or international). The effects are also moderated by consumer cosmopolitanism. The study has multiple theoretical and managerial implications. © 2020 Elsevier Ltd

Religion is known for transforming human behaviour in many ways. This research investigates the influence of religiosity on two unrestrained buying constructs; impulsive and compulsive buying. The focus of this paper is on both intrinsic and extrinsic dimensions of religiosity. The first study provides important insights into the differential impact of these two dimensions of religiosity on unrestrained buying constructs. The second study explores the underlying mechanism of the relationship between extrinsic religiosity and unrestrained buying behaviours. Results show a negative relationship of intrinsic religiosity and a positive relationship of extrinsic relationship with unrestrained buying constructs. We also found that this relationship for extrinsic religiosity is mediated by susceptibility to interpersonal influence and moderated by long-term orientation. This research explains the differential impact of religion on unrestrained buying behaviour. © 2020 Elsevier Ltd

The ongoing COVID-19 outbreak has revealed vulnerabilities in global healthcare responses. Research in epidemiology has focused on understanding the effects of countries’ responses on COVID-19 spread. While a growing body of research has focused on understanding the role of macro-level factors on responses to COVID-19, we have a limited understanding of what drives countries’ responses to COVID-19. We lean on organizational learning theory and the extant literature on rare events to propose that governance structure, investment in healthcare infrastructure, and learning from past pandemics influence a country's response regarding reactive and proactive strategies. With data collected from various sources and using an empirical methodology, we find that centralized governance positively affects reactive strategies, while healthcare infrastructure and learning from past pandemics positively influence proactive and reactive strategies. This research contributes to the literature on learning, pandemics, and rare events. © 2020 Elsevier Inc.

The purpose of this paper is to explore the human resource management (HRM) practices adopted by hotels during COVID-19 and to examine the impact of COVID-19 on the wellbeing of hotel employees using qualitative thematic analysis. This study presents HRM practices that organizations can use to effectively manage employees in uncertain times. There is compelling evidence that employee-centered HRM practices strongly impact employee wellbeing. This paper integrates the insights from an HRM framework for wellbeing using a job demands-resources model. The paper identifies themes that confirm and extend existing theories and models of wellbeing. The findings are important for policy makers by offering guidance for managing people effectively during tough times. © 2020 Elsevier Ltd

We provide causal evidence that regulation induced product shocks significantly impact aggregate demand and firm performance in pharmaceutical markets. Event study results suggest an average loss between $569 million and $882 million. Affected products lose, on average, $186 million over their remaining effective patent life. This leaves a loss of between $383 million and $696 million attributable to declines in future innovation. Our findings complement research that shows drugs receiving expedited review are more likely to suffer from regulation induced product shocks. Thus, it appears we may be trading off quicker access to drugs today for less innovation tomorrow. Results remain robust to variation across types of relabeling, market sizes, and levels of competition. © 2020 Elsevier B.V.

Intensive care unit (ICU) is a critical resource in a hospital, especially in developing countries such as India. The length of ICU stay after a cardiac surgery is an important variable for effective use of this critical resource. In this context, a predictive model can help a hospital to make optimum use of its ICU occupancy. A study was thus conducted on ICU patients and data gather over a 1-year period in a hospital in India. The critical factors for prolonged ICU stay (more than 72 h) were identified using univariate and multivariate logistic regression and a predictive index was built based on model development set. The predictive index was tested on a validation set and the mean length of ICU stay appeared to increase with an increase in the risk score. In addition, the risk score was tested in case of mortality. Efficient use of the ICU facility is possible with the help of this predictive index. © 2020, Operational Research Society of India.

The asymmetric vehicle routing problem with simultaneous pickup and deliveries is considered. This paper develops four new classes of valid inequalities for the problem. We generalize the idea of a no-good cut. Together, these help us solve 45-node randomly generated problem instances more efficiently. We report results on a set of benchmark instances in literature. In this set, we are able to show an order of magnitude improvement in computational times over currently published results in literature. © 2019 Elsevier B.V.

The purpose of this note is to serve as a revision to the article by Al-Salamah (2016). We offer two modifications to the above paper. First, we demonstrate that the inventory computations by Al-Salamah (2016) are not entirely consistent with the process mentioned, as they do not account for the defective items sent to the primary market, and hence we offer a revision for the same. Second, we show that for non-destructive testing, the expected proportion of defective items in the accepted and rejected lots will be different from that of the production process, which is not accounted for in the original article. Finally, we demonstrate the impact of these revisions through numerical examples. After updating the sensitivity analysis with the proposed modifications, for the parameters used, expected cycle time values show similar trend for both destructive and non-destructive testing, which were otherwise different in the original paper. © 2020 Elsevier Ltd

In this paper, it is shown that the polynomially bounded enumerative procedure to solve the facility location problem with limited distances, originally described by Drezner, Mehrez, and Wesolowsky [Drezner Z, Mehrez A, Wesolowsky GO (1991) The facility location problem with limited distances. Transportation Sci. 25(3):183–187.], and subsequently corrected by Aloise, Hansen, and Liberti [Aloise D, Hansen P, Liberti L (2012) An improved column generation algorithm for minimum sum-of-squares clustering. Math. Programming 131(1–2):195–220.], can still fail to optimally solve the problem. Conditions under which the procedures succeed are identified. A new modified algorithm is presented that solves the facility location problem with limited distances. It is further shown that the proposed correction is complete in that it does not require further corrections. Copyright: © 2020 INFORMS

Injuries related to road traffic are the major causes of death among people in the age bracket of 15–29 years (World Health Organization 2015). In many developing countries, motorized two-wheelers are the dominant means of transport and contribute to a more significant proportion of road fatalities. Leading causes of death are wounds to the head and neck that account for 88% fatalities in developing countries. India comprising of a significantly considerable percentage (70%) of two-wheelers with weak enforcement of helmet laws and poor compliance poses further challenges. This paper is divided into three sections. Section one reviews the literature on compliance behaviour from different theoretical disciplines to understand the behavioural factors that motivate compliance behaviour with the law. The second section reviews the empirical literature on helmet compliance across various countries with a mandatory helmet law. The overview brings to light that mere presence of a helmet law does not motivate compliance behaviour and more often lead to “token compliance”. The meaning of helmet use should be properly understood through in-depth interviews to understand the motivations to comply. The third section focuses on the evolution of helmet law in India. The overview suggests that regulations focus heavily on penalty structure and withdrawal of license as the primary disincentive to motivate compliance. Finally, alternative approaches to increase helmet compliance are discussed, and a regulatory framework that recognizes the coexistence of law, morality and social norm is suggested. © 2020, Springer Nature Singapore Pte Ltd.

Promoting active ageing has emerged as a key objective of urban planning and policymaking globally. Our study aims to provide new insights from a time-use perspective. In this paper, we use Hong Kong as a case study to investigate how people aged 60 and older allocate their time in various out-of-home activities. We analyse how personal and household characteristics affect the duration of out-of-home activities among older adults using two decennial time-use surveys. We focus on the influence of employment status and age because of policy relevance, particularly since the Hong Kong Government is considering extending the retirement age from 60 to 65. Comparison of time-use and activity participation between 2002 and 2013 suggests that employment status is positively associated with the duration of out-of-home activities and travel in both cross-sections; it also explains change over time. Findings also underscore the role of gender, age, education, type of housing, tenure of accommodation, household size, and income in determining older people’s activity–travel patterns. Our study shows that government policies to increase the share of employed people in the 60-years-and-older cohort and changes in the sociodemographic makeup of older people owing to various economic or societal forces could alter older people’s time-use and out-of-home activity patterns. Our study suggests that Hong Kong and other cities in the Asian region and beyond must aim at creating inclusive, age-friendly communities with adequate access to various activity opportunities in order to enhance quality of life in an ageing society. © 2020 Hong Kong Geographical Association.

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”.

Public acceptance constitutes an important factor in successfully establishing and operating nuclear power plants. This paper explores public attitudes to the Kudankulam Nuclear Power Project commissioned in 2013 and situated in Southern India, through assessing the role of socio-demographic factors, externalities, and social trust in determining the level of public acceptance. An exploratory survey (n = 100) was carried out in two administrative units in the vicinity of the plant. The study reveals that acceptance of the plant is positively correlated with positive externalities and trust in governmental entities, whereas negative externalities and trust in antinuclear nongovernmental organizations and media are associated with negative public perception. The results show that governmental policies on nuclear power must support the effects of positive externalities and reduce the effects of negative externalities. © 2020 John Wiley & Sons, Ltd

Purpose: In the context of sharing economy, the superhost program of Airbnb emerges as a phenomenal success story that has transformed the tourism industry and garnered humongous popularity. Proper performance evaluation and classification of the superhosts are crucial to incentivize superhosts to maintain higher service quality. The main objective of this paper is to design an integrated multicriteria decision-making (MCDM) method-based performance evaluation and classification framework for the superhosts of Airbnb and to study the variation in various contextual factors such as price, number of listings and cancelation policy across the superhosts. Design/methodology/approach: This work considers three weighting techniques, mean, entropy and CRITIC-based methods to determine the weights of factors. For each of the weighting techniques, an integrated TOPSIS-MOORA-based performance evaluation method and classification framework have been developed. The proposed methodology has been applied for the performance evaluation of the superhosts (7,308) of New York City using real data from Airbnb. Findings: From the perspective of performance evaluation, the importance of devising an integrated methodology instead of adopting a single approach has been highlighted using a nonparametric Wilcoxon signed-rank test. As per the context-specific findings, it has been observed that the price and the number of listings are the highest for the superhosts in the topmost category. Practical implications: The proposed methodology facilitates the design of a leaderboard to motivate service providers to perform better. Also, it can be applicable in other accommodation-sharing economy platforms and ride-sharing platforms. Originality/value: This is the first work that proposes a performance evaluation and classification framework for the service providers of the sharing economy in the context of tourism industry. © 2020, Emerald Publishing Limited.

We model a sustainable supply chain with simultaneous consideration of greening and Corporate Social Responsibility by supplier and buyer and analyze it for four different decision alternatives. In the first two cases, a single supply chain agent looks after both greening and social responsibility, in the other two cases, one agent takes one of the responsibilities. We compared these four cases by considering both full information and asymmetric information about the buyer's marginal production cost. Using the supplier Stackelberg game, we obtained the optimal values of decision variables under both information scenarios. The supplier negotiates with the buyer using the wholesale price contract or the linear two-part tariff contract. The second one is the dominating choice. For this contract the value of information is also higher for all decision alternatives. We have revealed the conditions under which the supplier would be benefited by choosing the greening effort and where the buyer would be benefited by taking up social responsibility. Further, we have designed a cut-off policy and found that the supplier and buyer can trade without conflicts only at a high level of consumer sensitivity towards greening and social responsiveness. This result suggests that if sustainability is left completely on consumer pressure, then the supplier and the buyer may not incorporate sustainability in the supply chain practices. We could specify those consumer sensitivity levels under which there must be government regulations to derive sustainability. © 2020 Elsevier B.V.

We conduct a case study of highway system performance in Los Angeles County. We use the Los Angeles Archived Data Management System, a comprehensive archive of regional real-time multi-modal transportation system data, to analyze effects of systematic, functional, random, and land use factors on performance variation over different time periods of the day. To understand functional class effects, we use cluster analysis on geometric and demand parameters to identify functionally similar groups of highway segments. We compare performance between groups and across segments within groups. We perform regression analysis to test the influence of various factors on performance. We find that after controlling for time of day, accidents, and adjacent population density, group or peer effects have significant influence. This suggests that peer group level, as opposed to regional, performance measurement and monitoring is useful. Our research has significant implications for transportation system monitoring and planning. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

Population-based optimization algorithms, such as evolutionary algorithms, have enjoyed a lot of attention in the past three decades in solving challenging search and optimization problems. In this chapter, we discuss recent population-based evolutionary algorithms for solving different types of bilevel optimization problems, as they pose numerous challenges to an optimization algorithm. Evolutionary bilevel optimization (EBO) algorithms are gaining attention due to their flexibility, implicit parallelism, and ability to customize for specific problem solving tasks. Starting with surrogate-based single-objective bilevel optimization problems, we discuss how EBO methods are designed for solving multi-objective bilevel problems. They show promise for handling various practicalities associated with bilevel problem solving. The chapter concludes with results on an agro-economic bilevel problem. The chapter also presents a number of challenging single and multi-objective bilevel optimization test problems, which should encourage further development of more efficient bilevel optimization algorithms. © 2020, Springer Nature Switzerland AG.