bluuebunny/crossref_metadata_2025_split huggingface dataset:
Individual investors' responses to mutual fund fire sales and sell-side analysts' price-correcting revisions
Authors: Jiang Jinglin , Wang Weiwei 
Published: July 2021

PurposeThis paper investigates individual investors' responses to stock underpricing and how their trading decisions are affected by analysts' forecasts and recommendations.Design/methodology/approachThis empirical study uses mutual fund fire sales as an exogenous source that causes stock underpricing and analysts' forecasts and recommendations as price-correcting information. The study further uses regression analysis to examine individual investors' responses to fire sales and how their responses vary with price-correcting information.FindingsThe authors first show that individual investors respond to mutual fund fire sales by significantly decreasing net buys, and this effect appears to be prolonged. Next, the authors find that the decrease of net buys diminishes following analysts' price-correcting earnings forecast revisions and stock recommendation changes. Hence, the authors suggest that individual investors are not “wise” enough to recognize flow-driven underpricing; however, this response is weakened by analysts' price-correcting information.Originality/valueThere is an ongoing debate in the literature about whether individual investors should be portrayed as unsophisticated traders or informed traders who can predict future returns. The authors study a unique information event and provide new evidence related to both perspectives. Overall, our evidence suggests that the “unsophisticated traders” perspective is predominant, whereas a better information environment significantly reduces individual investors' information disadvantage. This finding could be of interest to both academic researchers and regulators.
An investigation of employee perception of micro-corporate social responsibility and societal behavior: a moderated-mediated model
Authors: Mahmud Appel , Ding Donghong , Ali Zulqurnain 
Published: July 2021

PurposeThe micro-level research investigating employees' attitudinal, behavioral and psychological reactions to corporate social responsibility (CSR) has recently been expanded within CSR literature. Based on two interrelated social psychological theories, such as the theory of social information processing and the theory of social learning, this study examines the impact of perceived CSR–community (PCSRc; a micro-CSR area) on societal behavior (SB; a micro-level social work) at the employee level of analysis.Design/methodology/approachThis study recruited 440 bank employees of Bangladesh through a survey method and ran structural equation modeling to test the proposed measurement model and structural relationships in AMOS.FindingsThe study's outcomes report that PCSRc is positively related to SB and CSR engagement (CSRe). CSRe is also positively related to SB, and CSRe mediates the association of PCSRc and SB. CSR positivity (CSRp) moderates the direct relationship between PCSRc and CSRe and the indirect connection between PCSRc and SB via CSRe such that these relationships are significant when CSRp is high as compared to low.Research limitations/implicationsThis study focuses on highly educated employees' perception of micro-CSR initiative on micro-level social behavior in a newly emerging market context such as Bangladesh only.Practical implicationsThis study's outcomes guide policymakers to adopt CSR policy and its implementation strategies, accordingly, to employees' attitudinal, behavioral and psychological reactions to CSR.Social implicationsThis research can be used to steer the behavior of employees within society. It will eventually also have a positive influence on the perception of society toward the organization.Originality/valueThis study's originality is to find CSRe as a new intervening mechanism and CSRp as a new boundary condition of organizational CSR and employees' behavioral outcomes in the micro-CSR literature. The first study investigates the connections of three micro-constructs together, such as a micro (individual)-level analysis, a micro-CSR area and a micro-level social work setting.
Kaizen event process quality: towards a phase-based understanding of high-quality group problem-solving
Authors: Franken José C.M. , van Dun Desirée H. , Wilderom Celeste P.M. 
Published: July 2021

PurposeAs a problem-solving tool, the kaizen event (KE) is underutilised in practice. Assuming this is due to a lack of group process quality during those events, the authors aimed to grasp what is needed during high-quality KE meetings. Guided by the phased approach for structured problem-solving, the authors built and explored a measure for enriching future KE research.Design/methodology/approachSix phases were used to code all verbal contributions (N = 5,442) in 21 diverse, videotaped KE meetings. Resembling state space grids, the authors visualised the course of each meeting with line graphs which were shown to ten individual kaizen experts as well as to the filmed kaizen groups.FindingsFrom their reactions to the graphs the authors extracted high-quality KE process characteristics. At the end of each phase, that should be enacted sequentially, explicit group consensus appeared to be crucial. Some of the groups spent too little time on a group-shared understanding of the problem and its root causes. Surprisingly, the mixed-methods data suggested that small and infrequent deviations (“jumps”) to another phase might be necessary for a high-quality process. According to the newly developed quantitative process measure, when groups often jump from one phase to a distant, previous or next phase, this relates to low KE process quality.Originality/valueA refined conceptual model and research agenda are offered for generating better solutions during KEs, and the authors urge examinations of the effects of well-crafted KE training.
How to empower analytics capability to tackle emergency situations?
Authors: Akter Shahriar , Bandara Ruwan J. , Sajib Shahriar 
Published: July 2021

PurposeAnalytics thrives in navigating emergency situations. Emergency operations management needs to develop analytics empowerment capability (ANEC) to prepare for uncertainty, support continuity and tackle any disruptions. However, there is limited knowledge on ANEC and its effects on strategic emergency service agility (SESA) and emergency service adaptation (ESAD) in such contexts. Drawing on the dynamic capability (DC) theory, we address this research gap by developing an ANEC model. We also model the effects of ANEC on SESA and ESAD using SESA as a mediator. We also assess the moderating and quadratic effects of ANEC on two higher-order DCs (i.e. SESA and ESAD).Design/methodology/approachDrawing on the literature on big data, empowerment and DC, we develop and validate an ANEC model using data from 245 service systems managers in Australia. The study uses the partial least squares-based structural equation modelling (PLS-SEM) to prove the research model. The predictive power of the research model is validated through PLSpredict (k = 10) using a training sample (n = 220) and a holdout sample (n = 25).FindingsThe findings show that analytics climate, technological enablement, information access, knowledge and skills, training and development and decision-making ability are the significant components of ANEC. The findings confirm strategic emergency service agility as a significant partial mediator between ANEC and emergency service adaptation. The findings also discuss the moderating and quadratic effects of ANEC on outcome constructs. We discuss the implications of our findings for emergency situations with limitations and future research directions.Originality/valueThe findings show that building ANEC plays a fundamental role in developing strategic agility and service adaptation in emergency situations to prepare for disruptions, mitigate risks and continue operations.
Reducing retail supply chain costs of product returns using digital product fitting
Authors: Gustafsson Emmelie , Jonsson Patrik , Holmström Jan 
Published: July 2021

PurposeThis paper investigate how fit uncertainty impacts product return costs in online retailing and how digital product fitting, a pre-sales fitting practice, can reduce fit uncertainty.Design/methodology/approachThe paper analyzes the current performance of a retailer's e-commerce and return operations by estimating costs generated by product returns, including product handling costs, tied-up capital, inventory holding costs, transportation costs, and order-picking costs. The estimated costs were built on 2,229 return transactions from a Scandinavian fashion footwear retailer. A digital product fitting technology was tested with the retailer’s products and resulted in estimations on how such technology could affect product returns.FindingsThe cost of a return is approximately 17% of the prime cost. The major cost elements are product handling costs and transportation costs, which together amount to 72% of the total costs. If well calibrated, the fitting technology can cut fit-related return costs by up to 80%. The findings show how customers reacted to the fitting technology: it was unable to verify fit every time, but it serves as a useful and effective support tool for customers when placing orders.Research limitations/implicationsVirtual fit verification using digital product fitting is key to retailers to reduce fit-related returns. Digital product fitting using three-dimensional scanning is more appropriate for some products, but it is unsuitable for products that are difficult to measure and scan.Originality/valueThe paper contributes an empirical estimate of retail supply chain costs associated with fit uncertainty, as well as theoretical understanding of the role of pre-sales fit verification in avoiding product returns.
“I am OK when you are with me” – Understanding the well-being and innovative behavior in the digitized workspace
Authors: Karani Anushree , Mehta Swapnil Abhishek 
Published: July 2021

PurposeThe study aimed at understanding the relationship between supervisor and coworker support, psychological contract fulfillment, work engagement, well-being (different forms) and innovative behavior in the digitized workspace during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approachData were collected via a structured questionnaire through Google Docs from 239 respondents working in the sales department of the consumer durable industry through snowball sampling.FindingsSupervisor and coworker support was positively contributing to psychological contract fulfillment. Further, psychological contract fulfillment was positively contributing to work engagement. Along with innovative behavior, four forms of well-being, i.e. emotional, psychological, workspace and life were studied as outcome variables. Work engagement positively contributes to innovative behavior and well-being.Research limitations/implicationsThe study examined the relationship between various organizational variables in consumer durable industry. Future work should involve studying the effect in other industries and functional areas.Practical implicationsThe study examined how the supervisor and coworker act as an enabler in fulfilling the psychological contract in the digitized workspace. Organizations also understand the importance of work engagement in maintaining well-being and innovative behavior.Originality/valueThe paper initiates the important debate on well-being and innovative behavior in the digitized workspace for the sales employees of the consumer durable industry.
The moderating effect of person–organization fit on the relationship between job stress and deviant behaviors of frontline employees
Authors: Junaedi Marliana , Wulani Fenika 
Published: July 2021

PurposeThe purpose of this paper is to examine the relationship between job stress and deviant behaviors, which include organizational and frontline deviance, and the moderating effect of person–organization (P-O) fit on these relationships.Design/methodology/approachThe sample consists of 259 frontline employees working in Surabaya, Indonesia. Respondents were asked to complete a questionnaire distributed by survey assistants. This present study conducts partial least squares structural equation modeling to examine hypotheses.FindingsThe results indicate that job stress has positive correlations with organizational and frontline deviance. P-O fit has a moderating effect on the relationship between job stress and frontline deviance; the lower the P-O fit, the stronger the relationship between job stress and frontline deviance. P-O fit does not moderate the relationship between job stress and organizational deviance.Practical implicationsCompanies must be more careful in the recruitment and selection process and continuously perform activities to communicate their values and norms to employees.Originality/valueThis study introduces the moderating effect of P-O fit on the relationship between job stress and frontline employees' deviant behaviors, which has not been revealed in previous studies. It provides an understanding of the importance of considering the compatibility between individual and organizational values as one of the company's efforts to reduce stressed employees' responses by engaging in workplace deviance.
A unified blockchain-based platform for global e-waste management
Authors: Sahoo Swagatika , Mukherjee Arnab , Halder Raju 
Published: July 2021

Purpose
The rapid technological growth, changes in consumer demands, products’ built-in obsolescence, presence of more non-repairable parts, shorter lifespan, etc., lead to the generation of e-waste at an unprecedented rate. Although a number of research proposals and business products to manage e-waste exist in the literature, they lack in many aspects such as incomplete coverage of product’s life cycle, access control, payment channels (in few cases), incentive mechanisms, scalability issues, and missing experimental validation. The purpose of this paper is to introduce a novel blockchain-based e-waste management system aiming to mitigate the above-mentioned downsides and limitations of the existing proposals.

Design/methodology/approach
This paper proposes a robust and reliable e-waste management system by leveraging the power of blockchain technology, which captures the complete life cycle of e-products commencing from their manufacturing as new products to their disposal as e-waste and their recycling back into raw materials.

Findings
While the use of blockchain technology increases accountability, transparency and trust in the system, the proposal overcomes various challenges and limitations of the existing systems by providing seamless interactions among various agencies.

Originality/value
This paper presents a prototype implementation of the system as a proof-of-concept using solidity on the Ethereum platform and this paper performs experimental evaluations to demonstrate its feasibility and effective performance in terms of execution gas cost and transaction throughput.
Challenges of customer experience management in social commerce: an application of social network analysis
Authors: Jami Pour Mona , Hosseinzadeh Mahnaz , Mansouri Narjes Sadat 
Published: July 2021

PurposeAs social media applications have turned into popular platforms for interacting with customers, creation of a consistent customer experience in social commerce has attracted the attention of many practitioners and academics. The migration to create and manage customer experience in social commerce has become an essential issue that will bring new challenges for companies. Despite the increasing investment in this area, few studies have been conducted on the challenges of managing customer experience in social commerce. To fill this theoretical gap, the current study aims at comprehensively exploring the main challenges of customer experience management (CEM) in social commerce and investigating their importance and possible effects in relation to each other.Design/methodology/approachUsing the mixed method, first, the main challenges regarding CEM in social commerce were identified by reviewing the related literature. Then the challenges were enriched and categorized by expert opinions. Next, the challenges and the categorizations were confirmed by conducting a survey analysis applying thet-test and the factor analysis method. Afterwards, the main challenges were identified and weighted. Finally, the Social Network Analysis (SNA) approach was applied to investigate the causal relationship network among the challenges.FindingsThe results indicated that the main challenges of CEM in social commerce can be categorized into eight groups. Their weights and causal effects were calculated to identify the high priority challenges. By calculating the main SNA metrics such as degree and betweenness centralities, the high priority challenges of CEM in social commerce were identified. It was revealed that challenges with high out-degree centrality can create many other challenges and those with high betweenness centrality act as intermediary points, through which cause challenges may create effect challenges.Research limitations/implicationsThe research results can help marketers to get a big picture of the challenges to successfully implement CEM in social commerce and select the appropriate migration strategies more effectively. They are further recommended to pay due attention to customers' issues as well as the organizational challenges of CEM in social commerce.Originality/valueSocial media has become a priority for businesses to create and improve the customer experience; yet there is no tool to identify the challenges of CEM in this context. This study addresses the overlooked but critically important area of social commerce. The most important contribution of this research is an attempt to provide a comprehensive and integrated framework of the challenges in implementing CEM in social commerce and explore the causal effects they may have on creation of other challenges using SNA.
Interpretable video tag recommendation with multimedia deep learning framework
Authors: Yang Zekun , Lin Zhijie 
Published: July 2021

PurposeTags help promote customer engagement on video-sharing platforms. Video tag recommender systems are artificial intelligence-enabled frameworks that strive for recommending precise tags for videos. Extant video tag recommender systems are uninterpretable, which leads to distrust of the recommendation outcome, hesitation in tag adoption and difficulty in the system debugging process. This study aims at constructing an interpretable and novel video tag recommender system to assist video-sharing platform users in tagging their newly uploaded videos.Design/methodology/approachThe proposed interpretable video tag recommender system is a multimedia deep learning framework composed of convolutional neural networks (CNNs), which receives texts and images as inputs. The interpretability of the proposed system is realized through layer-wise relevance propagation.FindingsThe case study and user study demonstrate that the proposed interpretable multimedia CNN model could effectively explain its recommended tag to users by highlighting keywords and key patches that contribute the most to the recommended tag. Moreover, the proposed model achieves an improved recommendation performance by outperforming state-of-the-art models.Practical implicationsThe interpretability of the proposed recommender system makes its decision process more transparent, builds users’ trust in the recommender systems and prompts users to adopt the recommended tags. Through labeling videos with human-understandable and accurate tags, the exposure of videos to their target audiences would increase, which enhances information technology (IT) adoption, customer engagement, value co-creation and precision marketing on the video-sharing platform.Originality/valueThe proposed model is not only the first explainable video tag recommender system but also the first explainable multimedia tag recommender system to the best of our knowledge.
Pricing and coordination of vaccine supply chain based on blockchain technology
Authors: Liu Ruihuan , Tan Chunqiao , Zhao Chengwei 
Published: July 2021

PurposeVaccine safety is a major issue in the world. Blockchain technology is the right solution to this worldwide problem. The impact of introducing blockchain technology on the operational efficiency of the vaccine supply chain is unclear. Therefore, from the perspective of game theory, this paper aims to construct a vaccine supply chain model consisting of a vaccine manufacturer, a vaccine traceability service platform based on blockchain technology and a vaccination unit to discuss its pricing and coordination.Design/methodology/approachThis study analyzes the pricing and coordination of the vaccine supply chain based on blockchain technology, compares the decision-making of fixed charge scenario and proportional charge scenario and reveals the impact of blockchain on the vaccine supply chain.FindingsResults demonstrate that the revenue-sharing contract can coordinate the vaccine supply chain when the proportion of revenue sharing meets certain conditions. The fixed charge scenario is more beneficial to the vaccine supply chain than the proportional charge scenario. The introduction of blockchain technology increases the total profit, consumer surplus and social welfare of the vaccine supply chain. Therefore, the operational efficiency of the vaccine supply chain is improved.Originality/valueThis study not only provides important support for enterprises to adopt blockchain technology but also provides some guidance for decision-makers to implement scientific and feasible vaccine supply chain management schemes.
Types of politically connected firms and analysts' earnings forecast
Authors: Kamarudin Khairul Anuar , Wan Ismail Wan Adibah , Harymawan Iman , Shafie Rohami 
Published: July 2021

PurposeThis study examined the effect of different types of politically connected (PCON) Malaysian firms on analysts' forecast accuracy and dispersion.Design/methodology/approachThe study identified different types of PCON firms according to Wong and Hooy's (2018) classification, which divided political connections into government-linked companies (GLCs), boards of directors, business owners and family members of government leaders. The sample covered the period 2007–2016, for which earnings forecast data were obtained from the Institutional Brokers' Estimate System (IBES) database and financial data were extracted from Thomson Reuters Fundamentals. We deleted any market consensus estimates made by less than three analysts and/or firms with less than three years of analyst forecast information to control for the impact of individual analysts' personal attributes.FindingsThe study found that PCON firms were associated with lower analyst forecast accuracy and higher forecast dispersion. The effect was more salient in GLCs than in other PCON firms, either through families, business ties or boards of directors. Further analyses showed that PCON firms—in particular GLCs—were associated with more aggressive reporting of earnings and poorer quality of accruals, hence providing inadequate information for analysts to produce accurate and less dispersed earnings forecasts. The results were robust even after addressing endogeneity issues.Research limitations/implicationsThis study found new evidence of the impact of different types of PCON firms in exacerbating information asymmetry, which was not addressed in prior studies.Practical implicationsThis study has a significant practical implication for investors that they should be mindful of high information asymmetry in politically connected firms, particularly government-linked companies.Originality/valueThis is the first study to provide evidence of the impact of different types of PCON firms on analysts' earnings forecasts.