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.

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.

Social media platforms, owing to its great wealth of information, facilitates one's opportunities to explore hidden patterns or unknown correlations. It also finds its credibility in understanding people's expressions from what they are discussing on online platforms. As one showcase, in this paper, we summarize the dataset of Twitter messages related to recent demonetization of all Rs. 500 and Rs. 1000 notes in India and explore insights from Twitter's data. Our proposed system automatically extracts the popular latent topics in conversations regarding demonetization discussed in Twitter via the Latent Dirichlet Allocation (LDA)-based topic model and also identifies the correlated topics across different categories. Additionally, it also discovers people's opinions expressed through their tweets related to the event under consideration via the emotion analyzer. The system also employs an intuitive and informative visualization to show the uncovered insight. Furthermore, we use an evaluation measure, Normalized Mutual Information (NMI), to select the best LDA models. The obtained LDA results show that the tool can be effectively used to extract discussion topics and summarize them for further manual analysis.

In this paper, we propose a Novel Fuzzy-based Constructive Binary Neural Network (NF-CBNN) learning algorithm for multi-class classification. Our method draws a basic idea from Expand and Truncate Learning (ETL), which is a neural network learning algorithm. The proposed method works on the basis of unique core selection, and it guarantees to improve the classification performance by handling overlapping issues among data of various classes by using inter-cluster overlap. To demonstrate the efficacy of NF-CBNN, we tested it on the ORL face data set. The experimental results show that generalization accuracy achieved by NF-CBNN is much higher as compared to the BLTA classifier.

An exponential growth in the Indian e-commerce sector has attracted many national and international online retailers. Besides, price and promotional schemes, these e-retailers use website features-informativeness, entertainment and effectiveness of content, to differentiate from other players. This paper attempts to decipher the influence of hedonic and utilitarian shopping values and web atmospheric cues on e-satisfaction. From the survey findings, it is observed that web cues have greater influence in shaping e-satisfaction. Further, within the input variables effectiveness of information content has the largest influence on e-satisfaction. The study also highlights the importance of mediating role of e-satisfaction between shopping values, website features and e-loyalty. The paper suggests select marketing strategies for e-retailers.

In recent business practice, firms, to fulfill their IT requirements, are using both dedicated "on-premise" capacity infrastructure and "on-demand" capacity requirements provided by companies such as AWS, OpenStack, and VMware. In this research, we analyze the scenario where a business first invests in "on-premise" (or in-house) capacity and also procures the excess demand requirements through the public cloud provider utilizing the pay-as-you-go pricing model. We study the impact of factors such as demand correlation in buyers market and demand load profile on the capacity decision. We find various cloud computing strategies and link them with real-life business practices.

Purpose: Before initiating the implementation of change for transforming and improving an organization through lean thinking (LT), it has to first select a right value stream. Several implementation studies have been documented in literature, but not many studies have addressed this issue of value stream selection. The purpose of this paper is to propose and empirically validate a framework for selecting a value stream to implement LT. Design/methodology/approach: 8A framework is proposed by reviewing the literature on LT implementation case studies. Single case study methodology has been adopted to validate the application of 8A framework for selecting a value stream in an Indian educational institute. Since multiple qualifiers are considered simultaneously, a multi-criteria decision-making approach has been employed for choosing the value stream. Findings: Utility of the proposed 8A framework for value stream selection was confirmed through its successful application in an educational institute. Out of three alternatives in the case organization, the teaching alternative was chosen for further LT implementation based on the application of 8A framework. Qualitative cross-validation and sensitivity analysis also confirmed the robustness of the value stream selection made using the 8A framework. Research limitations/implications: Framework proposed in this study comprehensively captures the important qualifiers that were overlooked by the widely adopted first tenet of LT. Future research can attempt to generalize the applicability of 8A framework in different contexts including manufacturing, healthcare, software development, etc. A further study can be carried out in two similar case organizations or in two value streams of the same case organization (say in two different plants) to compare the differences in the outcome of lean implementation when one chooses its value stream for LT implementation without the application of the proposed framework, while another chooses it by applying the 8A framework. Practical implications: Through structured evaluation of the comprehensive set of qualifiers in 8A framework using a multi-criteria decision making model, an informed decision can be taken by the practitioners in selecting a value stream from the available alternatives before proceeding with the implementation of LT. Originality/value: After questioning the existing procedure of value stream selection for LT implementation, this study is the first to propose and validate an 8A framework that overcomes the limitations of the existing procedure. Study is also unique in the choice of the case organization as not many research papers have documented implementation of LT from the context of educational institutes.

Purpose: Before initiating the implementation of change for transforming and improving an organization through lean thinking (LT), it has to first select a right value stream. Several implementation studies have been documented in literature, but not many studies have addressed this issue of value stream selection. The purpose of this paper is to propose and empirically validate a framework for selecting a value stream to implement LT. Design/methodology/approach: 8A framework is proposed by reviewing the literature on LT implementation case studies. Single case study methodology has been adopted to validate the application of 8A framework for selecting a value stream in an Indian educational institute. Since multiple qualifiers are considered simultaneously, a multi-criteria decision-making approach has been employed for choosing the value stream. Findings: Utility of the proposed 8A framework for value stream selection was confirmed through its successful application in an educational institute. Out of three alternatives in the case organization, the teaching alternative was chosen for further LT implementation based on the application of 8A framework. Qualitative cross-validation and sensitivity analysis also confirmed the robustness of the value stream selection made using the 8A framework. Research limitations/implications: Framework proposed in this study comprehensively captures the important qualifiers that were overlooked by the widely adopted first tenet of LT. Future research can attempt to generalize the applicability of 8A framework in different contexts including manufacturing, healthcare, software development, etc. A further study can be carried out in two similar case organizations or in two value streams of the same case organization (say in two different plants) to compare the differences in the outcome of lean implementation when one chooses its value stream for LT implementation without the application of the proposed framework, while another chooses it by applying the 8A framework. Practical implications: Through structured evaluation of the comprehensive set of qualifiers in 8A framework using a multi-criteria decision making model, an informed decision can be taken by the practitioners in selecting a value stream from the available alternatives before proceeding with the implementation of LT. Originality/value: After questioning the existing procedure of value stream selection for LT implementation, this study is the first to propose and validate an 8A framework that overcomes the limitations of the existing procedure. Study is also unique in the choice of the case organization as not many research papers have documented implementation of LT from the context of educational institutes.

In recent business practice, firms, to fulfill their IT requirements, are using both dedicated on-premise capacity infrastructure and on-demand capacity requirements provided by companies such as AWS, OpenStack, and VMware. In this research, we analyze the scenario where a business first invests in on-premise (or in-house) capacity and also procures the excess demand requirements through the public cloud provider utilizing the pay-as-you-go pricing model. We study the impact of factors such as demand correlation in buyers market and demand load profile on the capacity decision. We find various cloud computing strategies and link them with real-life business practices.

In cloud service provisioning, spot instances are an attractive option for IT managers of small and medium enterprises (SMEs) that usually have sporadic requirements for cloud resources. Though priced dynamically, spot instances are usually cheaper. Cloud service providers (CSPs) employ the spot instance approach to sell their "idle" resources because spot instances are spare slots requiring no pre-booking, unlike reserved or on-demand instances that require prior booking. However, IT managers have to win spot instances via auctions conducted by CSPs. An SME continues to consume spot instances as long as its bid exceeds the current spot price. But, if it loses at any point in time, the unfinished task is to be put on hold by checkpoint mechanism. Optimizing both bid price and checkpoint overhead calls for strategic thinking on the part of the SME. This chapter dwells on this issue to help the IT managers of SMEs transform their business with cloud.

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.

For most managers, purchasing decisions are key decisions in the achievement of business organisation's strategic objectives. Appropriate supplier selection is necessary as it fulfils these important objectives of the organisation by maximising overall value to the purchaser, reducing uncertainty in supply, and by forming a long term, reliable relationship between buyers and suppliers. Supplier selection being affected by several conflicting factors requires an appropriate multi-criteria decision making approach. One of the recent approaches used for supplier selection is a hybrid data envelopment analytic hierarchy process (DEAHP) approach. However, this approach suffers from serious drawbacks as it uses counter intuitive priority vectors for inconsistent pair wise comparison matrices and also at times, it generate illogical weights for consistent pair wise comparison matrices as well. The objective of this paper is to present a revised DEAHP (RDEAHP) approach to overcome these drawbacks of DEAHP. The uniqueness of the research lies in the application of RDEAHP approach for supplier selection problem.

This paper proposes a new mathematical model for locating k-obnoxious facilities Here a vertex covering k-obnoxious facilities location problem on a plane has been modelled by combining it as a combination of three interacting criteria as follows: 1) maximise the minimum distances between any existing point and any variable point as well as between any pair of variable points; 2) maximise the number of existing points covered by various respective variable points; 3) minimise the overall importance of the various existing points associated to the various variable facility points. A nonlinear programming iterative algorithm for locating k-obnoxious facilities has been developed. The algorithm developed here is a generalised iterative algorithm. It has been proved that the optimal solution obtained by the algorithm is the non-dominated solution of the original multi-objective problem. Rectilinear distance norm has been considered as the distance measure as it is more appropriate to the various realistic situations.

In this paper we examine the stock market co-movement and volatility spillover dynamics in the Pacific developed markets for a period spanning over January 05, 2001 to January 09, 2018. We employ wavelet-based techniques to study the multiscale co-movement dynamics of stock returns. Additionally, we also study the subtleties of volatility spillover of returns among the sample countries. We find that: (a) diversification benefits in these markets are limited due to higher degrees of integration, (b) Pacific developed markets co-move strongly during the periods of financial crisis (i.e. the contagion hypothesis) and (c) higher degree of volatility spills during financial crisis. We believe our study holds significance in the perspective of international portfolio diversification.

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.

Returns of risky assets and their time-dependent volatility are often jointly modelled by stochastic volatility models (SVMs). Over the last few decades, several SVMs have been proposed to adequately capture the features of the relationship between the return and its volatility. The earliest SVM considers a hierarchical model, with current return as a function of the current latent volatility, which is further modelled as an auto-regressive process. In an attempt to make SVM more appropriate for complex realistic market behaviour, leverage parameter was introduced, which however led to violation of martingale difference property of the risky part of return (a necessary mean-zero condition that prevents arbitrage opportunities under mild regularity conditions). Subsequently, alternative SVMs had been developed and are currently in use. In this article, we propose mean-corrections for several generalizations of SVM with leverage that capture the complex market behaviour as well as satisfy martingale difference property of returns. We also establish a few theoretical results to characterize the key desirable features of these models, and present comparison with other popular competitors. Furthermore, three real-life examples (CITI bank stock price, euro-USD rate and S&P 500 index returns) have been used to demonstrate the performance of this new class of SVMs.

Purpose: The purpose of this paper is to introduce a new probability density function having both unbounded and bounded support with a wider applicability. While the distribution with bounded support on [0, 1] has applications in insurance and inventory management with ability to fit risk management data on proportions better than existing bounded distributions, the same with unbounded support is used as a lifetime model and is considered as an attractive alternative to some existing models in the reliability literature. Design/methodology/approach: The new density function, called modified exponential-geometric distribution is derived from the exponential-geometric distribution introduced by Adamidis and Loukas (1998). The support of the density function is shown to be both unbounded and bounded depending on the values of one of the shape parameters. Various properties of the density function are studied in detail and the parameters are estimated through maximum likelihood method of estimation. A number of applications related to reliability, insurance and inventory management are exhibited along with some useful data analysis. Findings: A single probability distribution with both unbounded and bounded support, which does not seem to exist in the reliability literature, is introduced in this paper. The proposed density function exhibits varying shapes including U-shape, and the failure rate also shows increasing, decreasing and bathtub shapes. The Monte Carlo simulation shows that the estimates of the parameters are quite stable with low standard errors. The distribution with unbounded support is shown to have competitive features for lifetime modeling through analysis of two data sets. The distribution with bounded support on [0, 1] is shown to have application in insurance and inventory management and is found to t data on proportions related to risk management better than some existing bounded distributions. Originality/value: The authors introduce an innovative probability distribution which contributes significantly in insurance and inventory management besides its remarkable statistical and reliability properties.

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.

Bilevel optimization is defined as a mathematical program, where an optimization problem contains another optimization problem as a constraint. These problems have received significant attention from the mathematical programming community. Only limited work exists on bilevel problems using evolutionary computation techniques; however, recently there has been an increasing interest due to the proliferation of practical applications and the potential of evolutionary algorithms in tackling these problems. This paper provides a comprehensive review on bilevel optimization from the basic principles to solution strategies; both classical and evolutionary. A number of potential application problems are also discussed. To offer the readers insights on the prominent developments in the field of bilevel optimization, we have performed an automated text-analysis of an extended list of papers published on bilevel optimization to date. This paper should motivate evolutionary computation researchers to pay more attention to this practical yet challenging area.