This research proposes a differential evolution-based regression framework for forecasting one day ahead price of Bitcoin. The maximal overlap discrete wavelet transformation first decomposes the original series into granular linear and nonlinear components. We then fit polynomial regression with interaction (PRI) and support vector regression (SVR) on linear and nonlinear components and obtain component-wise projections. The sum of these projections constitutes the final forecast. For accurate predictions, the PRI coefficients and tuning of the hyperparameters of SVR must be precisely estimated. Differential evolution, a metaheuristic optimization technique, helps to achieve these goals. We compare the forecast accuracy of the proposed regression framework with six advanced predictive modeling algorithms- multilayer perceptron neural network, random forest, adaptive neural fuzzy inference system, standalone SVR, multiple adaptive regression spline, and least absolute shrinkage and selection operator. Finally, we perform the numerical experimentation based on—(1) the daily closing prices of Bitcoin for January 10, 2013, to February 23, 2019, and (2) randomly generated surrogate time series through Monte Carlo analysis. The forecast accuracy of the proposed framework is higher than the other predictive modeling algorithms. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC part of Springer Nature.

This study examines the effects of competitive pressure by new entrants and technological discontinuity on the strategic innovations adopted by incumbent state-owned enterprises (SOEs) in India. Due to government ownership, these firms are dominant players domestically and their market leadership is challenged by new entrants. Technological discontinuity challenges technology leadership. Incumbent firms develop knowledge networks by working with partners, suppliers, and buyers. The incumbent firms must strike a balance between the exploitation of current technology and the exploration of new technology. This study aims to understand the effect of new entrants and technological discontinuity on the exploitation and exploration strategies of Indian SOEs in the manufacturing sector. The quantitative analysis is carried out using partial least squares structural equation modeling. For Indian SOEs, the technological discontinuity does affect exploitation and exploration, but new entrants have no such effect. The study confirms the moderating effect of knowledge networks on exploitation. © 2021 World Scientific Publishing Europe Ltd.

Multi-criteria decision-making (MCDM) techniques are being adopted in the supplier selection in the automotive industry. Due to their flexibility to interact with the factors needed in determining the supplier selection. The concept of a balanced scorecard is proposed for rating the supplier while evaluating their performance. Due to limitations in each MCDM technique, it is difficult to find a potential supplier using specific methodologies. Therefore, this paper proposes the integration of Fuzzy TOPSIS, Fuzzy AHP, and Fuzzy VIKOR in determining the potential supplier for a bus body building unit in the Indian context. After finding the rankings using each MCDM technique, spearman rank correlation coefficient is used to test the reliability in the ranks generated by each technique. The output results of this study help the company in establishing a robust supplier selection framework to select the best supplier. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Purpose: The purpose of this paper is to empirically examine the impact of the bank-appointed directors on the agency costs of debt by using the idiosyncratic risk of stock returns as a measure of agency costs of debt. Design/methodology/approach: We use multivariate panel regression, event study and finally, propensity score matching approaches to test our hypothesis. The robustness of the results is tested for possible endogeneity issues by employing instrumental variable two-stage least square (IV-2SLS) technique. Findings: Consistent with the efficient monitoring hypothesis, we find a negative relationship between the presence of the bank-appointed director and the idiosyncratic volatility of stock returns among Indian firms. This implies that such firms take up less risky investment projects. Originality/value: We contribute to the literature from two aspects. First, to the best of our knowledge, this is the first study that examines the monitoring efficiency of creditors' governance. Hitherto, such examinations are done from the shareholders' perspective. Second, we examine the role of the bank-appointed directors on the board of non-financial firms in an emerging world context and find, contrary to the existing evidence in the US context, active monitoring role played by such directors. © 2021, Emerald Publishing Limited.

Although the impact of job demands and work–family conflict (WFC) on burnout has been extensively discussed and analysed in the past literature, the role of WFC as a generative mechanism has been neglected. Therefore, the purpose of this study is to examine the mediating effects of WFC between job demands and burnout. The studied sample consisted of 713 Indian primary school government teachers who completed a self-report questionnaire assessing job demands, WFC and burnout. The results confirmed that WFC partially mediates the adverse association of job demands with burnout. Primary schools should, therefore, be encouraged to provide effective practices to manage work–family interfaces. © 2021 SAGE Publications.

In this paper, we analyze the inherent evolutionary dynamics of financial and energy markets. We study their inter-relationships and perform predictive analysis using an integrated nonparametric framework. We consider the daily closing prices of BSE Energy Index, Crude Oil, DJIA Index, Natural Gas, and NIFTY Index representing natural resources, developing and developed economies from January 2012 to March 2017 for this purpose. DJIA and NIFTY account for the global financial market while the other three-time series represent the energy market. First, we investigate the empirical characteristics of the underlying temporal dynamics of the financial time series through the technique of nonlinear dynamics to extract the key insights. Results suggest the existence of a strong trend component and long-range dependence as the underlying pattern. Then we apply the continuous wavelet transformation based multiscale exploration to investigate the co-movements of considered assets. We discover the long and medium-range co-movements among the heterogeneous assets. The findings of dynamic time-varying association reveal interesting insights that may assist portfolio managers in mitigating risk. Finally, we deploy a wavelet-based time-varying dynamic approach for estimating the conditional correlation among the said assets to determine the hedge ratios for practical implications. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.

Purpose: Access-based services (ABS) have been adversely impacted by the COVID-19 pandemic. This study aims to validate customer barriers to ABS focusing on the contamination barrier. As service employees’ presence violates the COVID-19 physical distancing norms and heightens contamination fear, this paper tests its effects on continued use intentions of ABS. This study also empirically examines the role of conspicuous virtue signaling and organizational response. Design/methodology/approach: The study was conducted in the context of scooter sharing and uses a mixed-method to explore the relatively under-researched problem of contamination fear in ABS. Study one uses the survey method and study two uses a 2 × 2 matrix between-subject design. Findings: The results reveal that perceptions of resource sufficiency positively affect continued use intentions of ABS. The presence of a service employee hurts continued use intentions. Further, there are a three-way interaction between ABS type (service employee presence/absence), organizational response (solution-oriented/general information) and resource sufficiency perceptions. Organizational response mitigates the negative effect of service employee presence on the link between resource adequacy perceptions and ABS continued use intentions. Originality/value: In contrast with prior research, this study shows that contamination fear invokes protection motivation, resulting in better preparedness and continued use intentions of ABS. The predicted difference is primarily between customers who attribute responsibility and ABS type differently (presence/absence of service employee). This study also explores the role of organizational response to COVID-19. © 2021, Emerald Publishing Limited.

The relationship between CSR and cash holdings is not conclusive from prior studies due to the endogeneity issue. In this study, we use a natural experiment setting, i.e., the implementation of mandatory CSR spending regulation in India in 2015, to test the relationship between CSR and cash holdings. Our results show a positive relationship between CSR and the value of cash holdings. As a result of such positive valuation, we observe that the firms which are required to spend on CSR activities under the Act, increased their cash level in the post-regulation period. © 2020 Elsevier Inc.

Purpose: This study aims to examine the correlates of burnout among primary school teachers working with public schools in Chhattisgarh-India. Design/methodology/approach: Data were collected from 713 teachers using a questionnaire survey. Using partial least square path modeling, this study tests the proposed measurement and structural model. Findings: The study confirmed that general job demands and emotional job demands in a school environment significantly correlated with burnout, which, in turn, has increased somatic symptoms and decreased pro-social behavior among teachers. However, the association of burnout with absenteeism was insignificant. Emotional intelligence (EI) was found to buffer the adverse associations of general job demands and emotional job demands on burnout. Practical implications: The findings of this study demonstrate that EI has buffering effects on high job demands that consequently reduce burnout. This will help educators and policymakers in shaping and formulating effective policies and practices to deal with burnout. Originality/value: Earlier studies exploring burnout of primary school teachers, especially in the Indian context, had focused exclusively on demographic factors. This study is an early attempt to understand the impact of contextual factors on burnout thereby helping in designing appropriate interventions thereof. This study additionally rationalizes the unexplored association of burnout with pro-social behavior among educators. © 2021, Emerald Publishing Limited.

We examine the effect of corruption on firm value using a comprehensive panel data set of 4236 firms with 38,763 firm-year observations from 16 emerging market economies during 2002–2015. By using fixed-effects panel data regression models, we find a significant negative relationship between firm value and corruption. The results are also robust to subsample analyses and to the alternate measure of firm value and corruption. Overall, our study provides evidence that corruption in emerging market economies has a negative impact on firm value. Furthermore, our study contributes to the existing literature on the drivers of firm value. ©, Copyright © Taylor & Francis Group, LLC.

Purpose: The governing role of bank-appointed directors (BADs) on the boards of non-financial firms has a potential to reduce information asymmetry between the firm and non-bank lenders. This should increase the confidence of other creditors in firm activities, thus performing the certification role. Therefore, the purpose of this paper is to empirically examine the certification role of BADs. Design/methodology/approach: The authors test their hypotheses by using a panel of Indian non-financial firms. Our approach involves examining whether there is a significant difference in the number of different debt sources, the dispersion of debt among different debt sources, and leverage for BAD and Non_BAD Firms. The authors use univariate analysis and multivariate regression models to test the difference. Findings: The authors find that firms with BADs on their board have (1) access to a higher number of different debt sources, (2) debt distributed evenly among different sources and (3) a higher debt ratio. Overall, our study provides supporting evidence for the certification role that BADs play on the boards of non-financial firms. Originality/value: The authors contribute to the literature in two aspects. First, to the best of our knowledge, this is the only study that examines the effect of the governing role of banks on the lending decisions of non-bank lenders. Second, our study is associated with the growing body of the governance literature in the emerging markets context by examining the interaction of financial policies and governance in an institutional framework, which is very different from that of the developed world. © 2020, Emerald Publishing Limited.

Hotel industry is the one which has confronted the unprecedented effect of the coronavirus disease 2019 (COVID-19) pandemic to significant social and economic risks. The COVID-19 pandemic has challenged the tourism across the globe and impacted hospitality in hotel industry severely. This study aims to assess customer satisfaction by carrying sentiment analysis and topic modelling over customer reviews on the hospitality provided by hotels in different continents during January to September 2020, i.e. the COVID-19 pandemic. We formulate an improved new scale of metrics to categorize customer satisfaction assessed by sentiment analysis in an elaborate way. Topic modelling was deployed to understand various topics most often discussed by customers. We find that North America and Europe could perform up to customer expectation. In Asia, Sri Lanka did well, Indonesia could maintain its customer satisfaction, while India consistently improved the satisfaction level. We identified 12 most discussed topics, and main reasons of dissatisfaction appear in staff, service, room, cleanliness, slow booking, and pandemic response by hotel. Findings of this study will help senior managers of hotels of developed as well as developing countries in providing new and effective services that can satisfy customers and restore their confidence. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

With the presence of fake reviews on e-commerce platforms, the reliability of reviews becomes questionable. The extant literature demonstrates the impact of fake reviews on product sales and proposes several algorithms to prevent fake reviews from being displayed on the platform. However, what has largely remained uninvestigated is how customers perceive reviews present on the e-commerce platform. Based on the speech act theory, we develop a theoretical framework that explains how the linguistic style (both at the word and the structural level) acts as a cue for assessing a reviewer's (in)sincere intentions. We evaluate the framework on a corpus of 120 online product reviews – each examined by at least 50 customers – using the fractional logit model. Results suggest that the communication style of a speaker reflects his/her intention. Reviews with less contextual embedding, argument structuring, and flattering through non-verbal cues trigger customers towards perceiving a review as deceptive. © 2020 Elsevier Ltd

Successful new product development projects and extant research literature advocate for inclusion of inputs pertaining to the supply chain at early stages of product development to proactively identify risk averse product design concepts. To this end, we devise an analytical framework to converge upon product design concept(s) that would be associated with lesser supply chain risks, usually function of both technical and commercialization considerations. The high-level and constituent lower-level supply chain risks are represented by parent and root nodes respectively within the devised Bayesian network driven research framework. Thereafter, a quantitative measure denoted as SCRI (supply chain risk index) is evolved that yields overall composite risk numbers corresponding to respective design concepts at different risk states. Validation and comparison of the devised method with an extant study illustrates the consistency and reliability of the study. It is found that the risk propensity of a particular design concept is inversely related to the probabilistic utility of that particular concept. The case of a construction power tool of a global firm is used to demonstrate the methodology. Our research addresses an important future research pathway as argued by Hosseini et al. (2020) that extant research literature is devoid of decision-making frameworks focused on measurement and analysis the propagation of risks on complex networks. © 2020 Elsevier Ltd

We propose “Deep Autoencoders for Feature Learning in Recommender Systems,” a novel discriminative model based on the incorporation of features from autoencoders in combination with embeddings into a deep neural network to predict ratings in recommender systems. The work has two major motivations. The first is to engineer features for recommender systems in a domain-agnostic way using autoencoders. The second is to develop a method that sets a benchmark for predictive accuracy. In our proposed solution, we build a user autoencoder and item autoencoder that extract latent features for the users and items, respectively. The additional features engineered are the latent features for the users and items, and these come from the bottleneck activations of the autoencoder. Our method of feature engineering is domain agnostic, as the inner-most activations would differ for domains without any additional effort required on part of the modeler. Next, we then use the activations of the inner-most layers of the autoencoders as features in a subsequent deep neural network to predict the ratings along-with user and item embeddings. Our method incorporates additional linear and nonlinear latent features from the autoencoders to improve predictive accuracy. This is different from the existing approaches that use autoencoders as full-fledged recommender systems or use autoencoders to generate features for a subsequent supervised learning algorithm or without using embeddings. We demonstrate the out performance of our solution on four different datasets of varying sizes and sparsity, namely MovieLens 100 K, MovieLens 1 M, FilmTrust and BookCrossing datasets, with strong experimental results. We have compared our DAFERec method against mDA-CF, TrustSVD, SVD variants, BiasedMF, ItemKNN and I-AutoRec methods. The results demonstrate that our proposed solution beats the benchmarks and is a highly flexible model that works on different datasets solving different business problems like book recommendations, movie recommendations and trust. © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.

In international business (IB), the level of equity ownership adopted by a firm is an important decision. In this study, we review and synthesize the findings of 105 empirical studies published in prominent IB and management journals on the determinants of equity ownership stake in foreign investment decisions, published between 1991 and 2020. Three primary theoretical lenses ? organizational learning perspective, transaction cost economics and institutional perspective – are adopted to catalogue and synthesize the existing literature. We find that, despite the proliferation of IB studies on antecedents of level of equity ownership decisions, many unanswered questions remain. We also find that theoretical fault lines impede progress in this research stream. Based on the literature review, we suggest a research programme that includes accounting for the behavioural view of decision-making in the organization, shifting from an atomistic perspective to a network perspective of the firm, having a better understanding of the process of internationalization and considering industry heterogeneity as well as the host country's characteristics. © 2021 British Academy of Management and John Wiley & Sons Ltd

Purpose: The main objective of this study is to evolve the basis of beneficial impact assessment of international marketing strategy (IMS) for emerging market multinationals by applying construct-measurement research methodology. The purpose of this study is to link the conceptual definition and empirical indicators of the proposed integrated model with the objective on “Developing Model to Assess Benefit Impacts Generated by International Marketing”, the authors named it GAMBIT. Design/methodology/approach: Self-administered questionnaires were used to collect data from international marketing executives and senior management executives from Indian manufacturing firms using Churchill's approach (1979, 1987). Exploratory and confirmatory factor analyses and structural equation modeling (using SPSS Statistics 20.0 and AMOS) were used to develop the GAMBIT model. Various hypotheses pertaining to perfect order fulfillment and quality level were formulated. Findings: In the order of significance, the four key influential factors for beneficial impact assessment in the multicultural global environment are as follows: sources of beneficial impacts; operational efficiency; international marketing strategic choice and beneficial outcomes. Originality/value: Although companies have realized the importance of assessing beneficial impacts, they often do not know how exactly the assessment should be made. Thus, the present study provides a useful tool for evaluating the totality of beneficial impacts offered by IMS. © 2020, Emerald Publishing Limited.

Using a sample of the listed firms over the period 2007–2019, we examine the impact of financial statement readability on the earnings management in a large emerging economy, India. Besides, we test for the readability of financially distressed and financially constrained firms. We use the fog index to measure the readability of the Management Discussion and Analysis (MDA) section of the annual report, and earnings management is measured using the Jones model. Our results indicate that the firms practicing earning management activities prepare lesser readable financial reports. Our results remain the same after adding the firm-fixed effect to control for firm-specific characteristics. Thus, more financial manipulation practices by the firm make the financial reports more complex to comprehend. © 2021 John Wiley & Sons Ltd.

Purpose: This study aims to analyze the influence of firm characteristics in dividend payout in a concentrated ownership setting. Design/methodology/approach: This study is probably the first to use the lasso technique for model selection and error prediction in the study of dividend payout in India. The lasso method comprises subsampling the available data set and performing reiterative regressions on those samples to generate the model with the best fit. This study incorporates four different ways of performing lasso treatment to get the best fit among them. Findings: This study analyzes the influence of firm characteristics on dividend payout in the Indian context and asserts that firms with growth potential and earnings volatility do not hesitate to cut dividends. This study does not find evidence for signaling, agency cost and life cycle theories in a concentrated ownership setting. Earnings is the single most important factor to have a positive influence on dividend, while excessively leveraged firms are restrictive of dividend payout. Taxation has a prominent role in altering the way firms pay dividend. Research limitations/implications: The recent changes in buyback taxation offer another opportunity to test the reactive behavior of firms. Also, given the disregard for traditional motivations, further research needs to be done to determine if dividend adjustments (on the lower side) help enhance firm value or not. Practical implications: This study may help investors view dividends in a proper perspective. Firms give importance to investments over dividends and thus investors need not dwell on dividend changes if firms fulfill their growth potential. Social implications: It lends perspective to investors about dividend changes and its importance. Originality/value: The methodology used for analysis is absolutely original in the literature pertaining to dividend policy in the Indian context. The literature is abundant with theories advocating or opposing the eminence of dividend payout; however, this study takes a holistic view of all influential dividend determinants in literature to understand dividend payout. © 2020, Emerald Publishing Limited.

Earlier researchers have observed that an individual consumer's mood plays a significant role in increasing the impulsiveness, which leads to impulsive buying. The literature on shoppers' motivational traits has profoundly acknowledged the impact of these traits and mood regulation constructs on individual shopping values. The present study is a pioneer attempt proposing a comprehensive model, which incorporates three main antecedents (motivation, mood and value) of buying behaviour that influence the consumer purchasing decision. The paper empirically explores the liaison between the regulatory focus (promotion-focused and prevention-focused motivations), mood regulation (mood monitoring, mood clarity and mood repair), shopping values (hedonic and utilitarian), and impulsive buying behaviour. The outcomes suggest that two regulatory focus motives influence mood clarity. Mood repairing and mood monitoring impact hedonic shopping values, which has a substantial impact on consumers' impulsive buying tendency. The paper closes with theoretical and practical inferences, limitations, and discussion on the potential scope for future research. © 2021 Elsevier Ltd