Recent studies in macro accounting suggest that changes in aggregate accounting earnings can predict quarterly GDP growth in the USA. Our objective in this study is to test the robustness of the association between aggregate earnings and real GDP growth across multiple countries and for different definitions of aggregate earnings. We test whether aggregate earnings changes predict future economic growth in eight countries–Australia, Canada, China, India, Japan, South Korea, the UK, and the USA. We find positive evidence regarding the generalisability of the aggregate earnings–real GDP relation in an international context. In additional tests, we find that economic forecasters appear to underreact to aggregate earnings information. Our results show that aggregate earnings lead economic growth and forecasts of real GDP growth can be improved by incorporating aggregate earnings information. Further, we also test if negative earnings changes contain more information than positive earnings changes and find only modest evidence in favour of this hypothesis. The results are robust to alternative statistical methodology and the removal of the USA data from the sample. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.

While there is much emphasis on authentic green practices, there is rising concern about the common practice of ''greenwashing'' or unsubstantiated claims about good environmental policies. Consequently, tourism businesses need to provide tangible evidences to create trust in their green claims. This paper, building on a sequential mixed method approach of data collection, proposes a potential green service encounter (GSE) framework by which hotel management can reassure customers and secure long-term patronage. Moderating role to two key contextual variables, travel purpose and environmental values of travelers, is investigated. Practical implications indicate that hotels should offer guests opportunities for enhanced involvement in GSE that help build consumer trust. The trust building process is dependent on a traveler's environmental values but independent of trip purpose. The GSE framework conceptualization included interviews with 25 green hotel guests and a panel of experts while empirical validation involved a sample of over 500 respondents.

Purpose: The purpose of this study is to systematically review and analyze the literature in the area of liquidity of financial markets. The study summarizes the key findings and approaches and highlights the research gaps in the extant literature. Design/methodology/approach: A variety of reputed databases are utilized to select 100 research papers, from a large pool of nearly 3,000 research papers spanning between 1972 and 2018 using systematic literature review methodology. The selected research papers are organized to provide an in-depth analysis and an account of the ongoing research in the area of liquidity. The study uses bibliometric network visualization and word-cloud analyses to compile and analyze the literature. Findings: The study summarizes the recent approaches in the liquidity research on aspects such as methodologies followed, variables applied, sub-areas covered, and the types of economies and markets covered. The article shows that the literature on liquidity in the emerging markets (e.g. China and India) is deficient. Overall, the following research areas related to liquidity need further exploration in the context of emerging markets: liquidity beyond the best bid-ask quotes, intraday return predictability using microstructure variables (e.g. order imbalances), impact of algorithmic-trading and volatility of liquidity. Originality/value: To the best of authors’ knowledge, in the recent past, a detailed account of the literature on liquidity has not been published. It provides a comprehensive collection and classification of the literature on the liquidity of financial markets. This would be helpful to the future researchers, academics and practitioners in the area of financial markets. © 2019, Emerald Publishing Limited.

In this paper, we propose a Generalised-Fuzzy-TOPSIS method as a versatile evaluation model. The model is suitable for different types of fuzzy or interval-valued numbers, with or without subjective weights of criteria being defined by evaluators. Additionally, we extend the final ranking step of the TOPSIS method, which is the calculation of closeness coefficient based on the separation from Negative Ideal Solution (NIS) and proximity to Positive Ideal Solution (PIS). Experiments show that with the same focus on PIS and NIS distances, our proposed ranking is identical to TOPSIS, and also performs very well when varying the distance weights. The applicability of the proposed method is demonstrated with relevant examples of technology and material selection in the context of additive manufacturing. Sensitivity analyses, based on subjective weights of criteria, degree of optimism, evaluators’ weights in group decision making, and distance weights, are presented to assist managers in making more informed decisions. © 2017 Elsevier Ltd

Ant colony optimization (ACO) algorithms have been used successfully to solve a wide variety of combinatorial optimization problems. In the recent past many modifications have been proposed in ACO algorithms to solve continuous optimization problems. However, most of the ACO variants to solve continuous optimization problems lack ability of efficient exploration of the search space and suffer from the problem of premature convergence. In this work a new ACO algorithm (ACO–LD) is proposed that incorporates Laplace distribution based interaction scheme among the ants. Also, in order to avoid the problem of stagnation, an additional diversification mechanism is introduced. The proposed ACO–LD is tested on benchmark test functions taken from Congress on Evolutionary Computation 2014 (CEC2014) and the results are compared with four state-of-the-art algorithms reported in CEC2014. ACO–LD is also applied to solve six real life problems and the results are compared with the results of six other algorithms reported in the literature. The analysis of the results shows that the overall performance of ACO–LD is found to be better than the other algorithms included in the present study. © 2017, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.

Purpose: The purpose of this paper is to examine the factors associated with three modes of firms’ exit (voluntary liquidation, involuntary liquidation and acquisition) in a mutually exclusive environment. In particular, three modes of exit are treated as independent events given that different causes and consequences exist for each exit mode. The data set is a panel of 4,408 US manufacturing firms spanning over the period 1976–1995. Design/methodology/approach: The discrete choice model is used to establish a relationship between modes of exit and a set of explanatory variables, which are specific to the firm, industry and macroeconomic conditions. Use of panel data encourages us to estimate a random effects multinomial logistic regression model, which allows exit modes as mutually exclusive events and at the same time controls the firm-specific unobserved heterogeneity in the sample. Findings: The analysis suggests that the determinants of voluntary liquidation are age, size, profitability, technology intensity and inflation level. The determinants of involuntary liquidation are size, leverage, profitability and inflation level. For acquisition, determinants are age, size, advertising intensity, Tobin’s q, GDP growth, inflation level and interest rate. The findings suggest that exit modes have a different set of determinants and the scale of effects of some common determinants such as age, size and profitability differs between exit modes. Research limitations/implications: The analysis presented in this study relies on data from US manufacturing firms only. Thus, there is a need to explore the determinants of exit modes in other countries as well using the proposed econometric model. Practical implications: The findings presented in this paper are useful for managers and policymakers to design strategies/actions for avoiding particular mode of exit. Originality/value: This study provides empirical evidence on the differences in factors associated with exit modes and confirms the existence of mutually exclusive nature of exit modes. Findings suggest that for future empirical studies on firm exit, the exit modes must be treated as a heterogeneous event. © 2018, Emerald Publishing Limited.

In the context of urban bus transport, the efficiency study of the bus routes, the impact of the contextual factors on the efficiency, and environmental performance measurement have not been paid enough attention. For performance evaluation, scholars mostly apply conventional data envelopment analysis (DEA) model whose limitation regarding handling the undesirable parameter limits its usefulness in the presence of undesirable outputs. Here, we propose a Shannon entropy-based output-oriented consolidated DEA model for the holistic performance measurements of the bus routes. Apart from operational and financial performance measurement, we introduce a novel ‘emission metric’ for environmental performance assessment of the bus routes. We show the context-specific implementation of several modified DEA models for measuring the efficiencies of the bus routes and integrate the efficiencies from different models into a single score using Shannon entropy approach. We apply the proposed method on 21 bus routes of Kolkata, an urban city in India. Our method facilitates consistent and more improved score in case of profit-making and loss-making routes, respectively. According to our analysis, route length, route overlapping, number of intermediate stoppages, and cost structure play a crucial role in the performance. We provide several route-specific as well as policy-level recommendations. © 2017 Canadian Operational Research Society (CORS).

Purpose: The purpose of this paper is to propose an approach to evaluate “on time” performance for a class of Indian railways (IR). This approach is build-up on the theme of six sigma level computation for continues data. The arrival data obtained from a class of IR called “Rajdhani Express” exhibited a unique characteristic: neither did the data followed a distribution nor could it be transformed to fit into a distribution. In this work, the authors present an approach to evaluate on time performance of IR, given such “unruly” data. Design/methodology/approach: An attempt is made to develop a lucid approach, given an unruly data. Initially, the authors plot a histogram using Scott’s method. Later, the authors use Taguchi’s quality loss function to assign weights to each of the bins in histogram. Weights to each of the bins are assigned based on the predefined rules. Finally, sigma level is computed by using weighted defect per million opportunities (DPMO) approach. In this paper, the authors discuss the proposed algorithm, an illustrative example with an emphasis on a class of IR. Findings: Given the unique characteristic (unruly data) of arrival data of IR, the proposed methodology helps in quantifying it is on time performance. This method extends the conventional DPMO approach of computing the sigma level. The proposed method is validated using various data sets of different distributions. Further, this approach can be generalized and applied to data set of any distribution. Since distribution of the data is not the pre-requisite, the proposed approach can be applied to compare (and benchmark) data sets of different distributions. This methodology, thus, paves path to develop newer approaches in quantifying and benchmarking the sigma levels. Research limitations/implications: In this manuscript, the authors present a case of Rajdhani Express trains, a class of IR. A practicing manager can use this approach to compare the performance of various classes of railways and benchmark their performance. Such an approach, with suitable modifications (if any) can be applied to evaluate performance in various service industries. Originality/value: Usually, if the data are unruly, the sigma level is computed by using ad-hoc methods that may provide compromising solutions and/or inaccurate results. The developed methodology proposes a unique approach to quantify sigma level, given such an unruly nature of the data. This approach thus fills the long needed gap in addressing such situations. This approach can be applied in various similar situations. A case of IR is presented. © 2018, Emerald Publishing Limited.

Interdependencies among healthcare providers result in complex healthcare supply chains with fragmented healthcare processes characterized by coordination failure and incentive misalignment. In developing countries where resources are scarce such coordination failures can have a severe impact on patient health. However, limited knowledge exists about how coordination takes place across and within the different healthcare service providers and how this influences hospital transfer time and length of stay. This article research this gap by studying trauma care delivery in India using a patient survey (n = 104). The Indian healthcare system is insightful because India has to provide low-cost care to large populations living in geographically big areas and the healthcare infrastructure struggles to meet increasing demands. The findings suggest mechanisms to better integrate the processes from the accident site to the hospital which include setting up referral processes, 24-hour ambulance services, using third-party coordinators and process improvement within the hospital following lean principles. © 2018 Indian Institute of Health Management Research.

Teenagers are major contributors of online content because of continuous communication and sharing with peers using social media or instant messaging apps. They like to immediately tell the world about their purchases and consumption experiences, which leads to the generation and transmission of electronic word-of-mouth (eWOM). This study uses consumer socialization perspective to examine how age, peers and Internet usage influence teenagers’ eWOM intentions. The findings suggest that normative and informative influence of peers and the Internet have significant positive association with eWOM. Moreover, these influences also mediate the direct influence of age and Internet usage on eWOM. Further, the potential eWOM behavior of male teenagers is influenced by the existing peer norms, whereas for females, their reliance and belief in the credibility of online information is more critical. The insights are valuable for marketers interested in the powerful and growing teenage consumer segment, especially in the new emerging markets. © 2017 Elsevier Inc.

Predicting software defects in software systems at early stages of its development has always been a very crucial and desirable aspect of software development industry. Today the machine learning algorithms are playing a massive role in classifying and predicting the possible bugs during the design phase. In this research work, the authors have proposed a discretization method based on metrics threshold values in order to gain better classification accuracy on a given data set. For the experimentation purpose, the authors have chosen the defect data sets from NASA repositories. In this Jedit, Lucene, Tomcat, Velocity, Xalan, Xerces software systems have been considered for experimentation using WEKA. The authors have also considered object-oriented CK metrics specifically for the study. Two very common and popular classifiers namely Naive Bayes and voted perceptron for the classification purpose. In the proposed work, various performance measures like ROC, RMSE values have been considered and analyzed. The results show that classification accuracy improvements can be made while using proposed discretization method with both classifiers. © Springer Nature Singapore Pte Ltd. 2018

Purpose: This paper aims to explore the trends, distribution and pattern of Indian bilateral cross-border joint venture (CBJV) activity with advanced developed nations (G7 nations) which include the USA, the UK, Japan, France, Germany, Italy and Canada over the 2001-2010 period. Design/methodology/approach: Longitudinal data on the population of 201 CBJVs are analyzed using Securities Data Company (SDC) platinum database. Chi-square test of independence is conducted on the parameters for CBJVs collected over a span of 10 years to test interrelations between them. Findings: The results of explorative trend analysis and test of interdependence are significantly different from developed countries in terms of interrelation between parent’s nationality, industry classification, broad purpose, period of formation and the equity owned. Research/limitations implications: Future work may explore the strategic motivation of both developed and developing nation firms, given the dynamics of CBJVs explored in this paper. The study could also be extended to other developed and developing nation firms CBJVs with Indian firms. Practical implications: This study provides a broad-based objective exploratory study of trends and distribution of CBJVs from the standpoint of the developing nations. This helps managers to identify the dynamic industries of CBJVs in India as far as G7 nations are concerned. Social implications: The possibility of asymmetric motives of partners in CBJV could not be negated. The role of Indian policymakers also becomes much larger to regulate the monopolistic and anti-competitive practices. Originality/value: The longitudinal study serves to present first of its kind systematic analysis of detailed activity of Indian firms in bilateral CBJV formation. © 2018, Emerald Publishing Limited.

With industrialization and growth of population, implementation of sustainable technologies and environment protection has received a lot of attention. Remanufacturing is one of the sustainable technologies that provide environmental, economic and social benefits. Remanufacturing is “a comprehensive and rigorous industrial process by which a previously sold, worn, or non-functional product or component is returned to a “like-new” or “better-than-new” condition and warranted in performance level and quality” (RIC, 2013). This research study aims to identify and evaluate external barriers to remanufacturing in Indian electronic waste (e-waste) sector. We applied grey-DEMATEL (Decision Making Trial and Evaluation Laboratory) approach to analyze external barriers to remanufacturing. The results indicate lack of channels to collect used products and customer unwillingness to return the products to be the most prominent barriers. Further, the results also depict uncertainty in quantity and timing of returned products to be the major causal barriers. The findings provide insights and recommendations for policy planners involved in policy making to boost remanufacturing in India. Primarily, government needs to bring awareness to customers regarding benefits of returning the used products and benefits of using remanufactured products through awareness campaigns, so that consumers also take initiative to protect environment. Channels to collects used products from customers also need to be developed. © 2018 Elsevier B.V.

Purpose: The purpose of this paper is to examine the relationship between implementation of quality management systems (QMS) and business performance, through mediating factors (operating performance, information quality, product quality, design performance, environmental performance and competitive priorities). Most of the published literature examines the direct impact of implementation of QMS on business performance, and on some of the above stated factors. However, the impact of implementation of QMS on business performance, through these mediating factors has not received much attention. Accordingly, the authors develop a theoretical framework depicting impact of implementation of QMS on business performance through the above stated factors. Design/methodology/approach: The paper proposes several hypotheses linking implementation of QMS, mediating factors and business performance. The hypothesized model is empirically tested using data collected from 120 professionals working in quality engineering/management in India and North America. The collected data are analyzed with the aid of structural equation modeling (SEM) technique. Findings: Information quality and design performance have emerged as the important factors in the research. Information quality directly effects design performance, operating performance and environmental performance. The model indicates that besides a well-designed product, managers need to focus on the operating performance to improve overall product quality. Empirical evidence is found regarding direct and indirect effect of implementation of QMS on above stated mediating factors and on business performance. Originality/value: The research fills a gap in the literature by considering several mediating factors that aid in improving business performance with implementation of QMS. © 2018, Emerald Publishing Limited.

Purpose: Emotions in business-to-business (B2B) interactions are relatively unexplored when compared with business-to customer (B2C) industry wherein sufficient evidence implicating the role of emotions in decision-making is available. This study aims to explore the role of emotions in B2B decision-making, and a customer experience model is suggested for the B2B industry. Design/methodology/approach: The qualitative research methodology using structured and semi-structured interviews along with a repertory grid technique was followed during the study. Purposive sampling was done to identify respondents who were involved in the vendor choice process either as a buyer or a seller in their respective organizations. Findings: Exploratory research conducted during this study supports the presence of five dimensions of customer experience – sensory, emotional, relational, behavioural and intellectual – in a B2B context. The study further indicates that the experiential value for B2B decision-making is derived from functional, symbolic, emotional and cost values which are assessed by the buyer during their interaction with the product or the service ecosystem and has an impact on the purchase intentions of an industrial buyer. Originality/value: This paper identifies the role of specific customer experience dimensions in a B2B environment and proposes the role and mechanism of emotional factors affecting the decision-making process in B2B exchange. © 2018, Emerald Publishing Limited.

We test if seven commonly used asset-pricing factors predict future growth in GDP and industrial production. There is minimal evidence that asset-pricing factors other than the market factor predict future economic growth. Predictive power of these factors reported in earlier literature seems to have attenuated. © 2018 Elsevier B.V.

This study used a quantile autoregressive distributed lag (QARDL) model to capture asymmetric impact of rainfall on food production in India. It was found that the coefficient corresponding to the rainfall in the QARDL increased till the 75th quantile and started decreasing thereafter, though it remained in the positive territory. Another interesting finding is that at the 90th quantile and above the coefficients of rainfall though remained positive was not statistically significant and therefore, the benefit of high rainfall on crop production was not conclusive. However, the impact of other determinants, such as fertilizer and pesticide consumption, is quite uniform over the whole range of the distribution of food grain production. © 2016, Springer-Verlag Wien.

Purpose: From last few decades, logistics management (LM) constitutes a global concern among organization’s supply chain (SC) to improve their business effectiveness. The purpose of this paper is to uncover and analyze the critical factors (CFs) related to the implementation of effective LM concept and benchmark the SC performance. Design/methodology/approach: The most common (16) CFs were identified and selected through literature and use of the Delphi method. Subsequently, the selected most common CFs were analyzed to distinguish their causal relations using the fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) technique under unclear surroundings. A case example of Indian Logistics Company is also discussed to reveal the practical applicability of the research. Findings: Provision of the effective information communication and technological developments in the system and Management dedication, support and involvement CFs are found to have the top most influences in the effective implementation of LM. This paper also groups the CFs into cause and effect relationship which provides valuable insights for analyzing the factors in successful implementation of LM. Practical implications: This work attempts to understand the different CFs, their relative position and the importance rating in the system, due to which, managers can differentiate the factor which greatly affects the concepts of implementing LM, and thus, improvements can be made accordingly. Originality/value: First, this work offers 16 CFs to LM implementation from a SC scenario. Second, in the context of contributing to the theory, the combined Delphi and fuzzy DEMATEL-based model is provided that helps in managing the logistic related issues effectively. © 2018, Emerald Publishing Limited.

Purpose: The purpose of this paper is to facilitate green supply chain (GSC) managers and planners to model and access GSC risks and probable failures. This paper proposes to use the fuzzy failure mode and effects analysis (FMEA) approach for assessing the risks associated with GSC for benchmarking the performance in terms of effective GSC management adoption and sustainable production. Design/methodology/approach: Initially, different failure modes are defined using FMEA analysis, and in order to decide the risk priority, the risk priority number (RPN) is determined. Such priority numbers are typically acquired from the judgment decisions of experts that could contain the element of vagueness and imperfection due to human biases, and it may lead to inaccuracy in the process of risk assessment in GSC. In this study, fuzzy logic is applied to conventional FMEA to overcome the issues in assigning RPNs. A plastic manufacturer GSC case exemplar of the proposed model is illustrated to present the authenticity of this method of risk assessment. Findings: Results indicate that the failure modes, given as improper green operating procedure, i.e. process, operations, etc. (R6), and green issues while closing the loop of GSC (R14) hold the highest RPN and FRPN scores in classical as well as fuzzy FMEA analysis. Originality/value: The present research work attempts to propose an evaluation framework for risk assessment in GSC. This paper explores both sustainable developments and risks related to efficient management of GSC initiatives in a plastic industry supply chain context. From a managerial perspective, suggestions are also provided with respect to each failure mode. © 2018, Emerald Publishing Limited.

This paper introduces a bi-criteria transportation problem with multiple parameters which brings together the concept of price discrimination from the area of marketing management to the world of multi objective transportation problems. The problem deals with two objectives, the overall shipment cost and the bottleneck time of shipment. Both the objectives are of minimization type and have multi-choice coefficients pertaining to differential marketing strategies or different modes of transportation available. First, the problem with minimum availability and demand of goods is solved and then the problem is extended to the case of interval demand and supply. By iteratively solving multi-choice variants of a cost minimizing transportation problem/minimum cost flow problem, all Pareto optimal time–cost pairs are obtained. The proposed algorithm for both the variants is successfully implemented and solved using the CPLEX optimization package. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.