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Casual selling practice: a qualitative study of non-professional sellers' involvement on C2C social commerce platforms
No full textInternational audiencePurpose Recent substantial developments of consumer-to-consumer social commerce platforms (C2C-SCPs) emboldened consumers/users to be involved as sellers. Considering C2C social networks that privilege local reach, this paper aim to explore how the practice-based view informs non-professional sellers' involvement. Design/methodology/approach Underpinned by data from 29 semi-structured interviews with non-professional sellers on Kaskus, one of the largest local Indonesian C2C-SCPs, the study reveals the emergence of a novel structural practice that we call casual selling. Findings The findings show that casual selling allows non-professional sellers' involvement in C2C-SCPs through three broad categories of practices: priming oneself, producing commercial operations and valuing others. Within these three categories, non-professional sellers are found to generate both personal and collective involvement along nine situated market practices. Research limitations/implications This paper adds to previous research by introducing the practice-based view to social commerce literature. In doing so, it deals with the under-investigated seller's perspective and activities that prevail in C2C-SCPs. Originality/value In C2C-SCPs, casual selling constitutes a distinct mode of involvement in social commerce in which established professional selling standards are suspended. As a structural practice, it entices non-professional sellers to consider a wider variety of situations in which they are in dialogue with other individuals (buyers and sellers) to shape s-commerce potential. In doing so, C2C-SCP users draw on a dynamic intertwining between digital technology and the socio-cultural environment surrounding s-commerce
Antecedents of intentions to crowdfund luxury brands and projects: Evidence from French consumers
No full textInternational audienceLuxury firms, including high-end watch manufacturers, use crowdfunding as an alternative source of entrepreneurial finance. Respondents indicated that intention to crowdfund luxury brand start-ups have both external and internal antecedents with the slight majority focusing on the extrinsic factors. The “luxury” proposition exhibits integrated motivation, which is conceptualized and personalized to the tastes of each investor
When Relationships Get in the Way: The emergence and persistence of care routines
No full textInternational audiencePast research has shown that routines can be a vehicle for both stability and change in organizations. It is unclear however how this relationship alters and solidifies over time. In this paper, the changing behaviours of three newly formed teams within a domiciliary care organization are tracked over a period of two years. It was seen that self-reinforcing processes shaped the emergence and persistence of action patterns within these groups. The first process achieved coordination benefits which drove the emergence of routines, as ‘action patterns’ were first negotiated and then assigned to members of the care team. The second self-reinforcing process involved sets of expectations which deepened interpersonal relationships between the care worker and client. The impact of both these processes, altered the ostensive-performative duality, as routines emerged and persisted over time. This study therefore highlights the changing dynamics of stability and change within routines, and the key role played by social relations in this process
Corporate social responsibility and firm market performance: the role of product market competition and firm life cycle
No full textInternational audienceThis study empirically investigates the role of product market competition and mature-stage firm life cycle on the relation between corporate social responsibility (CSR) and market performance in an emerging market context – Malaysia. The authors construct a comprehensive CSR index toward the economy, environment and society (EES) and apply both Ordinary Least Squares (OLS) and Two-Stage Least Squares (2SLS) instrumental variables (IV) approaches to test the hypotheses of the study. The authors find that EES-based CSR generally enhances firms' market performance; however, the level of product market competition undermines the market performance of socially and economically responsible firms. In addition, the study results indicate that mature-stage firm life cycle with more involvement in CSR activities shows better market performance. However, the endogeneity check of CSR suggests that both CSR and mature-stage firms are mutually exclusive in influencing market performance. The study findings are robust to alternative measures and different identifications of high and low default risk situations of sample firms. Practical implications This study carries practical policy implications for the listed firms, regulators and stakeholders in general. For example, regulatory bodies may promote greater involvement in CSR activities by listed companies in the Malaysian stock market. Investors and other market participants should be aware of factors influencing socially responsible firms' market performance such as the corporate life cycle and the level of competition in product markets. This research work responds to the call of regulatory bodies in Malaysia at a time when the Malaysian economy is under threat of environmental distraction practices by the palm oil industry and import ban by the largest export market, i.e. the European Union by 2030. The study also contributes to the theoretical literature by refining the moderating role of product market competition and mature-stage life cycle on the relationship between CSR and market performance from the perspectives of resource-based and stakeholder theories in emerging economy settings
Blockchain technology in the supply chain: An integrated theoretical perspective of organizational adoption
No full textInternational audienceBlockchain technology has been growing in importance and acceptability over the past few years. Yet, there is limited empirical research on the organizational and technology specific factors that play a critical role in driving its adoption in the supply chain. The purpose of this paper is to develop a comprehensive framework for blockchain adoption in the supply chain by identifying the enablers and empirically evaluating their interdependencies and impact on adoption. 20 enablers of blockchain adoption in the supply chain are identified using an extensive literature review and theoretical lenses from the Diffusion of Innovation (DOI) theory and the business technology adoption model developed by Iacovou, Benbassat and Dexter (1995). In the confirmatory phase, we employ the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to extract logic from data collected from 37 French experts about the impact of the enablers and their interdependencies. Our paper extends the multi-theoretic empirical studies to blockchain technology and identifies the enablers of blockchain adoption from technological, organizational, supply chain and external environment perspectives. Regarding the importance of the categories of enablers, we find that the relative advantage of the technology and the external pressure are the most prominent categories of enablers that impact blockchain adoption in the supply chain. Our analysis also shows the important causal role on adoption of the potential of blockchain to reduce transaction cost, the consumer interest in traceability data and the establishment of a regulatory framework for blockchain usage
Regulatory Spillovers and Data Governance: Evidence from the GDPR
No full textInternational audienceWe document short-run changes in websites and the web technology industry with the introduction of the European General Data Protection Regulation (GDPR). We follow more than 110,000 websites and their third-party HTTP requests for 12 months before and 6 months after the GDPR became effective and show that websites substantially reduced their interactions with web technology providers. Importantly, this also holds for websites not legally bound by the GDPR. These changes are especially pronounced among less popular websites and regarding the collection of personal data. We document an increase in market concentration in web technology services after the introduction of the GDPR: Although all firms suffer losses, the largest vendor—Google—loses relatively less and significantly increases market share in important markets such as advertising and analytics. Our findings contribute to the discussion on how regulating privacy, artificial intelligence and other areas of data governance relate to data minimization, regulatory competition, and market structure
Do corporate governance mechanisms curb the anti-environmental behavior of firms worldwide? An illustration through waste management
No full textInternational audienceDriven by the current surge in environmental and climate issues and the pressure of the government and regulatory bodies on corporations to diminish their carbon trails, this study uniquely examines the impact of distinct corporate governance mechanisms on the level of waste produced on a global sample of firms during 2002-2019. Our findings show that corporate governance mechanisms are important predictors of the level of waste produced by firms worldwide. In particular, the board size, board independence, and sustainability committees are linked to a higher level of waste produced. Conversely, the board gender diversity reduces the waste produced, and CEO duality is not associated with the level of waste produced. Our results are robust to alternate proxies of main variables, potential endogeneity concerns (using propensity score matching, two-stage least squares, and generalized system method of moments technique), and additional analyses. Further analysis shows that larger and gender-diverse boards improve the firm’s waste recycling behavior, whereas board independence and the presence of a sustainability committee are negatively related to waste recycling. The study has vital insinuations in developing efficient, ethical regulations and guidelines for corporate boards specifically from the perspective of waste management, environmental protection, and restoration
A Novel Machine Learning Approach for Predicting the NIFTY50 Index in India
No full textInternational audienceOver the past decade, extensive research on stock market prediction using machine learning models has been conducted. In this framework, different approaches for data standardisation methods have been used for financial time series analysis and to assess the impact of data standardisation on the final prediction outcome. The paper uses the feature-level optimal rolling-window batch data standardisation method to improve the machine learning model's predictive power significantly. Along with the standardisation method, the paper explores the performance of the automated feature interactions learner (Deep Cross Networks) effect on a plethora of technical indicators aiming at predicting the movements of the NIFTY50 index in India, as these predicted changes are reflected in options contracts
A new hybrid machine learning model for predicting the bitcoin (BTC-USD) price
No full textInternational audienceSeveral machine learning techniques and hybrid architectures for predicting bitcoin price movement have been presented in the past. Our paper proposes a hybrid model encompassing classification and regression models for predicting bitcoin prices. Our analysis found that the automated feature interactions learner (deep cross networks) error performance using a plethora of technical indicators, including crypto-specific technical indicator difficulty ribbon compression and control variables such as Metcalfe’s value of bitcoin, number of unique active addresses, bitcoin network hash rate, and S&P 500 log returns, in a hybrid architecture is better than the single-stage architecture. The hybrid model predicted a 100% directional hit rate and maintained steady volatility in returns for the out-of-sample period. Our paper concludes that in terms of risk (Sharpe ratio 1.03) and profitability (260% and 82%), the hybrid model’s bitcoin futures strategy performed better than the deep cross network regression and buy-and-hold benchmark strategies