Data-driven approaches have noteworthy significance in managing and improving logistics in E-commerce enterprises. This study focuses on the development of an integrated framework to analyse the Brazilian E-Commerce enterprise public dataset. From the analysis, it is found that sellers of Ibitinga city of SP state had the most count of late deliveries where 42 sellers are under-performing in terms of estimated delivery time. Locations of customers and sellers were spotted on a map to get a geographical representation. The proposed framework may help E-Commerce enterprise owners and retail merchants to make better decisions related to sales and E-Commerce enterprise logistics. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

We employ Data Envelopment Analysis to estimate the new technical, new cost, and new profit efficiency of Indian banks over the period 2008–2018. Then, we use Random Forest Regression to examine the impact of corporate governance (Board Size, Board Independence, Duality, Gender Diversity, and Board Meetings), bank characteristics (Return on Assets, Size, and Equity to Total Assets), and other characteristics (Ownership and Years) on bank efficiency. Among others, we found that board characteristics play a significant role particularly in new profit efficiency; therefore, policymakers and regulators should consider Board Size, Board Independence, Board Meetings, and Duality while framing guidelines for enhancing bank new profit efficiency. We also found that Board Independence plays a vital role in bank new cost efficiency, while Gender Diversity contributes to both new technical and new cost efficiency. This study makes methodological contributions by employing Machine Learning based Random Forest Regression in tandem with Data Envelopment Analysis under a two-phase model to examine corporate governance and bank efficiency, which is a pioneering attempt. © Operational Research Society 2021.

5G communication is the most trending technology and nowadays commercialized to the whole world. Still, now is the time to look forward beyond this technology that could be more forward than 6G. It is the improved technology for future applications and also for emerging space and terrestrial equipment. It is a unique opportunity for people to progress in various sectors like education, health, environment, business, and many more. The 6G is the sixth generation of mobile and telecommunication systems. The six genesis flagship program is the large-scale set up of eight-year research initiatives that implement the test and critical enabling technology for 6G. In this paper, the authors reviewed the technology advancement in the 6G network. This study shows the comparative analysis of efficient, cost-effective, and specific and aggregate efforts toward breakthrough innovations. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Purpose: This study aims to develop two sentiment indices sourced from news stories and corporate disclosures of the firms in the National Stock Exchange NIFTY 50 Index by extracting sentiment polarity. Subsequently, the two indices would be compared for the predictive accuracy of the stock market and stock returns during the post-digitization period 2011–2018. Based on the findings this paper suggests various options for financial strategy. Design/methodology/approach: The news- and disclosure-based sentiment indices are developed using sentiment polarity extracted from qualitative content from news and corporate disclosures, respectively, using qualitative analysis tool “N-Vivo.” The indices developed are compared for stock market predictability using quantitative regression techniques. Thus, the study is conducted using both qualitative data and tools and quantitative techniques. Findings: This study shows that the investor is more magnetized to news than towards corporate disclosures though disclosures contain both qualitative as well as quantitative information on the fundamentals of a firm. This study is extended to sectoral indices, and the results show that specific sectoral news impacts sectoral indices intensely over market news. It is found that the market discounts information in disclosures prior to its release. As disclosures in quarterly statements are delayed information input, firms can use voluntary disclosures to reduce the communication gap with investors by using the internet. Managers would do so only when the stock price is undervalued and tend to ignore the market and the shareholder in other cases. Otherwise, disclosure sentiment attracts only long horizon traders. Practical implications: Finance managers need to improve disclosure dependence on investors by innovative disclosure methodologies irrespective of the ruling market price. In this context, future studies on investor sentiment would be interesting as they need to capture man–machine interactions reflected in market sentiment showing the interplay of human biases with machine-driven decisions. The findings would be useful in developing the financial strategy for protecting firm value. Originality/value: This study is unique in providing a comparative analysis of sentiment extracted from news and corporate disclosures for explaining the stock market direction and stock returns and contributes to the behavioral finance literature. © 2021, Emerald Publishing Limited.

Traffic problems across the major cities around the world and the ever-growing population have put immense stress on countries’ smart infrastructure needs and requirements, particularly in emerging economies such as India. In such countries, existing urban transport modes have failed to accommodate the rising travel demand, which means traffic congestion will likely multiply further in the coming years. This distressing situation creates opportunities for automobile and aircraft makers to develop state-of-the-art urban air mobility (UAM) solutions. The electric vertical take-off and landing (eVTOL) vehicles seem to represent the future of urban mobility. Commercialized air taxis have the potential to completely disrupt the urban transportation system and relieve the urban streets from congestion. The case discusses the factors facilitating a speedy drift towards adopting air taxis and the recent developments in the UAM industry. To explore the air taxi market opportunities and business feasibility, the case examines the UAM ecosystem, the related cost and technology components, the industry's latest competitive landscape, and anticipated barriers to the successful implementation of the air taxi business. The case outlines allied businesses and complementary revenue streams that the UAM sector would encourage and, thus, help developing nations to grow technologically and economically. © 2022, Association for Information Systems. All rights reserved.

Global retail industry players have witnessed a grave scenario due to the impact of the COVID-19 pandemic. The pandemic has changed the way shoppers think, manifested in the decelerating footfall and increasing threat for traditional brick and mortar stores. The strategy of switching over to omnichannel seemed to have provided the needed relief to traditional retailers and manufacturers in the consumer goods industry. However, a robust omnichannel product assortment model requires integrating channels and remodeling managers’ roles to provide consumer experience and satisfaction and maximize profitability across all touchpoints with minor disruptions. The paper formulates and simulates an omnichannel data-driven fulfillment analytical model to analyze customers’ product mix and manage assortment accordingly. Further, an optimization model that maximizes revenue and profitability is formulated as a suggestive framework with strategies for the current scenario. The paper is helpful for marketing researchers and retail planners for omnichannel assortment management. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Purpose: This work reports on a study to measure tractor owners' (mostly farmers') repurchase behavior (RPB). While earlier studies have focused on the technical aspects of the tractors, none as yet have considered farmer intention and behavior for predicting purchase decision. A conceptual model was built considering all possible antecedents of farmers' RPB based on in-depth interviews and discussions with marketing managers. Interviews with customers were used to understand these antecedents or interactions with salespersons, either directly or indirectly during conversations or visits to stores. The authors have attempted to develop a scale on farmers' consumption experience from the perspective of farmers. Design/methodology/approach: The model was validated using Smart-PLS, and the best tractor brand was identified using data envelopment analysis (DEA). At the village level, snowball sampling was adopted to identify potential tractor owners who had repurchased the same brand or a higher model as respondents. Findings: Findings reveal that all the paths were found to be significant. Farmers' consumption experience (FE) seems to be the biggest predictor of RPB, followed by image, satisfaction and trust. The newly introduced construct FE has a significant effect on farmers' RPB. DEA results further indicate that most tractor companies function with 100% efficiency. Research limitations/implications: The study was carried out in India; it can be extended to other countries. Also, the sample was collected from one state in India and is cross-sectional in nature, so it cannot be generalized. Originality/value: First, the authors developed a conceptual model considering all possible antecedents of RPB. No studies had yet developed a scale on FE. Second, the authors created a benchmark for the various preferred tractor brands from the farmers' perspective using DEA. © 2020, Emerald Publishing Limited.

The organic food market has emerged as a growing trend among consumers. The present study examines the relationship between Health Consciousness (HC), Organic Food Knowledge (OFK), Subjective Norms (SN), Price Perception (PP), Environmental Concern (EC), Attitude (ATT), Willingness to Purchase (WP), and Actual Buying Behaviour (ABB) towards organic food. Furthermore, the study explores the mediating effects of ATT and WP in the relationship between the aforesaid variables and ABB. The data was collected from 240 respondents using convenience sampling approach. The Structure Equation Modelling (SEM) using ADANCO 2.2 is used to test the hypotheses of the conceptual model proposed in the present study. The study found that the variables HC, OFK, SN, EC, ATT, WP significantly affect the ABB. Also, it is observed that EC is the strongest predictor of ATT, WP, and ABB in organic food purchase, whereas PP is the least influencing factor. Further, HC positively influences ATT and WP but shows a negative association with ABB. The antecedents HC, OFK, SN, PP, EC has shown a significant indirect effect on ABB among respondents through ATT and WP. Finally, the theoretical and practical implications are discussed. © 2022 John Wiley & Sons Ltd.

The digital transformation fostered by the increasing leverage of artificial intelligence (AI) has been a critical influencing factor unleashing the next wave of enterprise business disruption. Marketing is one of the business streams witnessing this transformation on a very intense scale. Contemporary marketing has begun to experiment with modern, cutting-edge technologies, such as AI, deploying them in mainstream operations to ensure accelerated success. This article explores the use of AI in marketing as an emergent stream of research. Based on inferences from earlier studies, the study categorizes marketing into five distinct functional themes—integrated digital marketing, content marketing, experiential marketing, marketing operations, and market research—and 19 sub-functional themes (activity levers). Across the chosen themes and sub-themes, the study further dovetails into and identifies 170 featured use cases of the extant literature, where AI is leveraged by marketing in delivering superior quality outcomes and experiences. By way of a systematic literature review (SLR), the article evaluates 57 qualifying publications in the context of AI-powered marketing and qualitatively and quantitatively ranks them based on their coverage, impact, relevance, and contributed guidance, and elucidates the findings across various sectors, research contexts, and scenarios. The study discusses the practitioner and academic research implications and proposes a future research agenda to study the continuous transformation fostered by accelerated adoption of AI across the marketing landscape. © The Author(s) 2021.

This paper explores the economic consequences of non-pharmaceutical government intervention to curb disease spread on Indian commodity-level exports. This is the first study to assess the export implications of the pandemic using a panel linear as well as a novel non-linear ARDL framework. Our results show that pandemic-related stringencies have a positive effect on Indian exports in the long-run. This result holds valid for domestic as well export destination countries? stringencies. However, our evidence suggests that reducing stringencies has a more dominating effect on Indian exports than tightening of stringencies. Also, stringencies and uncertainty impact exports adversely in the short-run. Furthermore, pandemic-related financial uncertainty is found to have a dampening effect on exporting. Our results also show a significant asymmetric impact of policy responses on exports, especially for agriculture and manufacturing commodities, while mineral products are relatively less impacted. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

One of the significant challenges in the sports industry is identifying the factors influencing match results and their respective weightage. For appropriate recommendations to the team management and the team players, there is a need to predict the match and quantify the important factors for which prediction models need to be developed. The second thing required is identifying talented and emerging players and performing an associative analysis of the important factors to the match-winning outcome. This paper formulates a hybrid machine learning-clustering-associative rules model. This paper also implements the framework for cricket matches, one of the most popular sports globally watched by billions around the world. We predict the match outcome for One day Internationals (ODIs) and Twenty 20 s (T20s) (two formats of Cricket representing fifty over and twenty over versions respectively) adopting state-of-the-art machine learning algorithms, Random Forest, Gradient Boosting, and Deep neural networks. The variable importance is computed using machine-learning techniques and further statistically validated through the regression model. The emerging talented players are identified by clustering. Association rules are generated for determining the best possible winning outcome. The results show that environmental conditions are equally crucial for determining a match result, as are internal quantitative factors. The model is thus helpful for both team management and for players to improve their winning strategy and also for discovering emerging players to form an unbeatable team. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

This paper estimates the efficiency of value added by banks using their total resources (physical capital resources and intangible resources) and finds an association between board characteristics and efficiency of value added. The paper is grounded in the theory of resource and knowledge based view of the firm, and agency theory, and tries to establish links between these two theories. This study departs from existing literature of examining the effect of board characteristics on financial performance, corporate sustainability, and corporate environmental responsibility, and tries to understand the relationship between board characteristics and the efficiency of value added by banks through their resources. This is also the first study of its kind to study the relationship between board structure characteristics and value creation in Indian banks using the Value Added Intellectual Coefficient (VAIC) methodology. Using the data for 41 commercial banks in India from 2008 to 2017 and by employing Prais-Winsten Regression, this study finds that board meetings and CEO-Chairman duality significantly and positively influence the efficiency of value added by banks through their total resources and intellectual capital resources. At the same time, independence in the boards negatively influences the efficiency of value added through physical capital resources. Overall, the findings of the paper indicate that board governance influences bank performance measured in terms of efficiency of value added. Policymakers, regulators, and bank managers should frame appropriate policies to ensure more board meetings, and the presence of board duality. © 2022 Elsevier Inc.

Business continuity in disruptions like the COVID-19 pandemic involves sustainable supply chain management (SSCM) with limited resources and risks for the well-being and prosperity of stakeholders and customers involved with limited environmental effects. The purpose of the paper is to outline enablers in customer engagement that supports SSCM in times of disruption like the COVID-19 pandemic. This research uses an extensive literature review followed by academic and industry practitioners’ opinions to identify customer engagement enablers in SSCM for business continuity. Hybrid stepwise weight assessment ratio analysis (SWARA) and rough set numbers rank customer engagement enablers that support SSCM in disruption. The research builds on stakeholder theory and the sustainability framework for economic performance through non-economic aspects. The research concludes that the focus on agility for target customers through collaboration and information sharing in SSCM will support business continuity. It shall support decision-making in the supply chain in uncertainties. Engagement with stakeholders leads to focused execution in response to customer demand through faster communication and crucial information sharing, thus eliminating bottlenecks for business continuity. © 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Developing measures to capture customer sentiment and securing a positive customer experience is a strategic necessity to improve firm profitability and shareholder value. The paper considers the relationship between customer satisfaction, earnings, and firm value as these drives change in stock prices, customer, and investor sentiment. The present study investigates the impact of customer sentiment polarity on stock prices based on Indian automobile sector databased such as the Indian Nifty Auto SNE (Maruti Suzuki, Tata Motors, and Eicher). A top-down approach is adopted to construct a financial proxy-based sentiment index completed with sentiment extracted from automobile news and customer reviews. The paper uses a text mining approach to holistically measure customer sentiment's impact on investor sentiment and stock prices. The study was initially performed at the overall individual stock from the Nifty Auto NSE but focused on the top three passenger vehicle manufacturing companies i.e., Maruti Suzuki, Tata Motors, and Eicher. It was found that the sentiment index was augmented with news and customer reviews allows predicting more accurately NIFTY AUTO stock price movements. This implies that customer sentiment is a major driver of investor sentiment which in turn impacts the stock market and the firm value. Thus, the present study is an integrated approach to holistically measure customer sentiment's impact on investor sentiment and stock prices. © 2021

Purpose: Supply chain network is complicated to manage due to the involvement of a number of agents. Formation of virtual organization using Industry 4.0 (I4.0) is an approach to improve the efficiency and effectiveness and to overcome the complexities of the channel. However, the task of managing the channel further becomes complicated after incorporating sustainability into the supply chain. To fill this gap, this paper focuses on designing of mechanism and demonstration of I4.0-based virtual organization to coordinate sustainable supply chain. Design/methodology/approach: In this paper, we model and compare I4.0-based virtual organization models using four other traditional contracts with centralized supply chain. The non-cooperative game theoretic approach has been used for the analysis of models. Findings: Our game-theoretic analysis shows that investment in I4.0 and sustainable innovation are beneficial for the overall supply chain. Our results show that linear two-part tariff contract and I4.0-based virtual organization model can perfectly coordinated with the supply chain. Research limitations/implications: This study consider deterministic model settings with full information game. Therefore researchers are encouraged to study I4.0-based coordination models under information asymmetry and uncertain situations. Practical implications: The paper includes implications for the development of I4.0-based coordination model to tackle the problems of channel coordination. Originality/value: This study proposes I4.0-based game-theoretic model for the sustainable supply chain coordination. © 2021, Emerald Publishing Limited.

This study uses aspect-level sentiment analysis using lexicon-based approach to analyse online reviews of an Indian brand called Patanjali, which sells many FMCG products under its name. These reviews have been collected from the microblogging site Twitter from where a total of 4961 tweets about 10 Patanjali branded products have been extracted and analysed. Along with the aspect-level sentiment analysis, an opinion-tagged corpora has also been developed. Machine learning approaches - support vector machine (SVM), decision tree, and naïve bayes - have also been used to perform the sentiment analysis and to figure out the appropriate classifiers suitable for such product reviews analysis. The authors first identify customer preferences and/or opinions about a product or brand by analyisng online customer reviews as they express them on the social media platform Twitter by using aspectlevel sentiment analysis. The authors also address the limitations of scarcity of opinion tagged data required to train supervised classifiers to perform sentiment analysis by developing tagged corpora. © 2022, IGI Global.

Purpose: The present study aims to examine the moderation of the employee's age on the manifestation of “experience of hurt” to “commitment to future conflict” among the three intra-cohort segments of millennials. The study also examines the mediation of “perception of duplicitous organization” between hurt and “commitment to future conflict.” Design/methodology/approach: Cross-sectional data was collected using survey method and analyzed by structural equation modelling on SPSS AMOS 25 software. Findings: The results are based on single-source cross-sectional data. The result indicates that “perception of duplicitous organization” is positively impacted by the experience of hurt at the workplace. It also acts as a mediator between hurt and “commitment to future conflict”. There is significant moderation of age for all the relationships in the model. For instance, age moderates both the paths of hurt resulting in “perception of duplicitous organization” and aggressiveness, where the group of young employees have significantly higher path coefficients. Practical implications: The managers need to be more considerate and interact frequently with the younger employees as they are more prone to develop aggression and are impressionable to form a “perception of duplicitous organization” after an experience of hurt. The manager needs to establish a high-quality relationship and a positive image of the organization with subordinates to prevent the manifestation of hurt to a “commitment to future conflict”. Originality/value: To the best of the knowledge of the authors, this study is the first of its kind to study the moderation of age within the larger cohort of millennials. © 2021, Emerald Publishing Limited.

In a democratic country like India, citizens expect quality public services, from the government. The information technology-enabled versions of public services cannot be an exception. In order to develop strategies leading to increasing levels of satisfaction of the citizens, the quality of the services should be analyzed. For efficient and effective public service delivery, many countries all over the world attempt to develop the transparent and accountable online system to bring the citizen's faith in governance. The present study attempts to check that does the e-service quality of the online grievance redress portal satisfy the student users. Dimensions and construct of the proposed model were extracted from literature, a survey was conducted by employing a questionnaire, soliciting inputs from 677 respondents. Partial least squares structural equation modeling (PLS-SEM) modeling was used to drive the results. Results indicates that security and privacy, is the utmost significant dimensions for student satisfaction as it helps to develop trust in the online e-governance system to bring satisfaction that increases the usage of the grievance portal It is followed by reliability and delivery of quality of information. The demographic variable, gender observed to be not having a significant relationship with the students' satisfaction concerning e-government services. The limitations and future research scope of the study are also presented. © 2022 John Wiley & Sons Ltd.

On one hand, Industry 4.0-based sustainable manufacturing has been undergoing a revolution, and generating widespread interest both among business leaders and academicians, based on the assumption that it has a linear and direct relationship. On the other, sustainable ambidextrous innovation has become crucial in reducing carbon emissions, saving costs, and creating new market segments simultaneously. However, the research on the role of lean and sustainable manufacturing on Industry 4.0 adoption is developing, and literature has assumed a linear and direct relationship. Using Structural Equation Modeling, we investigate the mediating role of ambidextrous innovation capabilities on Industry 4.0 adoption in order to achieve sustainability goals across multiple businesses and stakeholders. In the process, we add to research on sustainable manufacturing and Industry 4.0, while making three salient contributions: (1) Scale development to measure constructs, such as lean manufacturing, sustainable manufacturing, innovation ambidexterity and Industry 4.0 adoption. (2) Establishing a relationship between lean & sustainable manufacturing and Industry 4.0. (3) Investigating the mediating role of innovation ambidexterity. © 2021

The seaports in China are the busiest in the world and facing challenges pertaining to environmental pollution, Green House Gases (GHG) emissions, damages to the marine ecosystem etc. To tackle these issues, the maritime community in China is looking for sustainable green solutions. One way forward is to establish green ports, but there is no reliable intelligence available on sustainability of such an idea. For that reason, this research aims to discern relevant sustainability factors for green ports development. Thereafter, the identified factors are assessed using FAHP (Fuzzy Analytic Hierarchy Process) method of MCDM (Multi-Criteria Decision-Making). The results indicate that the factors; Environment, Digitization, Automation, and Strategy are ranked top three censorious among six identified main categories of the factors. Further, sensitivity analysis is carried out to check the robustness of the applied method. The industry managers and policy makers must attentively monitor and adopt top ranked factors to establish sustainable green practices at Chinese ports. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.