Search results

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

This work aims to offer a better understanding of the inevitable challenges related to the digital transformation in the family-owned low-tech SMEs, examining the role assumed by familiness in this specific context. To this end, it examines the main factors that influence the adoption and implementation of digital technologies in the family-owned low-tech SMEs.

The study uses a multiple case studies approach, by investigating the case of family-owned low-tech SMEs operating in the winery sector and located in the South-Italy area.

Based on the empirical evidence, findings show how familiness influence the digital transformation of family-owned SMEs and highlight three main factors – individual, process and organization – relevant for the introduction and use of digital technologies in the productive and innovative activities of these organizations.

This paper fills the research gap existing in the literature on the family business. Firstly, it focuses on the digital transformation phenomenon and underlines how familiness, within family-owned low-tech SMEs, can differently influence the firm's innovation processes primarly based on the use of digital technologies oriented to enable business improvements. Then, it identifies diverse dimensions that can act as “barriers” or “facilitators” for adopting advanced digital technologies within the organizations here examined.

Artificial intelligence (AI) can help in defining preventive strategies in taking decisions in complex situations. This paper aims to research how workers might deal with intervening AI tools, with the goal of improving their daily working decisions and movements. We contribute to deepening how workers might deal with intervening AI tools aiming at improving their daily working decisions and movements. We investigate these aspects within a field, which is growing in importance due to environmental sustainability issues, i.e. waste management (WM).

This manuscript intends to (1) investigate if AI allows better performance in WM by reducing social security costs and by guaranteeing a better continuity of service and (2) examine which structural change is required to operationalize this predictive risk model in the real working context. To achieve these goals, this study developed a qualitative inquiry based on face-to-face interviews with highly qualified experts.

There is a positive impact of AI schemes in helping to detect critical operating issues. Specifically, AI potentially represents a tool for an alignment of operational behaviours to business strategic goals. Properly elaborated information, obtained through wearable digital infrastructures, allows to take decisions to streamline the work organization, reducing potential loss due to waste of time and/or physical resources.

Being a qualitative study, and the limited extension of data, it is not possible to guarantee its replication and generalizability. Nevertheless, the prestige of the interviewees makes this research an interesting pilot, on such an emerging theme as AI, thus eliciting stimulating insights from a deepening of information coming from respondents’ knowledge, skills and experience for implementing valuable AI schemes able to an align operational behaviours to business strategic goals.

The most critical issue is represented by the “quality” of the feedback provided to employees within the business environment, specifically when there is a transfer of knowledge within the organization.

The study focuses on a less investigated context, the role of AI in internal decision-making, particularly, for what regards the interaction between managers and workers as well as the one among workers. Algorithmically managed workers can be seen as the players of summarized results of complex algorithmic analyses offered through simpleminded interfaces, which they can easily use to take good decisions.

This study aims to analyse the influence of digitalisation on the management control function of small and medium-sized enterprises (SMEs). In particular, it aims to illuminate how digitalisation influences management control elements, organisation and roles/competencies and to identify obstacles to digitalisation of management control in SMEs and measures taken to overcome them.

The study is based on guideline-supported expert interviews conducted with 14 financial managers from SMEs in Germany, Austria and Switzerland.

This study reveals the influence of digitalisation on management control elements, organisation, and roles/competencies. The automation and standardisation of management control processes result in new elements for management control, such as strategic support for management. In addition, the increased availability and transparency of data enable the use of instruments within a company that allow for quick analyses of the company's development. Digitalisation leads to the integration of management control into the corporate network and, thus, a change in the organisation of management control. It also triggers the expansion of management control competencies, especially IT competencies. A shortage of internal digitalisation resources, unclear corporate roadmaps, and a lack of managerial experience loom as central challenges for digitalising the management control function. Measures derived from the interviews can help SMEs overcome the obstacles to the digitalisation of management control.

This research is the first interview-based study of the impact of digitalisation on management control in SMEs, potential obstacles to that digitalisation, and measures to overcome those obstacles. Thus, it contributes to the emerging debate on factors that may explain why SMEs lag in terms of the digitalisation of their internal processes.

Documentation plays a key role in navigating the costs of construction projects. Traditional document management systems (TDMS) used in developing countries, however, hinder the achievement of expected cost targets. Although the electronic document management system (EDMS) has been implemented to improve documentation, the Sri Lankan construction industry has failed to effectively adapt to it. Hence, this study aims to provide strategies for the effective application of EDMS to the cost management of Sri Lankan mega construction projects.

This study uses a qualitative approach followed by 12 semi-structured expert interviews. Quantity surveying experts were selected through judgemental sampling. Manual content analysis was used to analyse the data.

The EDMS is more suitable for megaprojects than traditional methods of documentation in terms of functionality, neutrality, interoperability, space, reversibility and delivery speed. However, there are contradictory views about cost and security. Furthermore, five transitional challenges of EDMS have been identified under the three key themes of cost, stakeholder perception and technical difficulties. Four reasons were also identified as causing these five challenges. Seven suggestions were made to deal with these transitional challenges and three key feasible solutions for the Sri Lankan construction industry regarding the EDMS were identified. Development of Sri Lankan software with low initial cost was highlighted as the most feasible solution.

This is a novel study to investigate the applicability of EDMS to cost management mechanisms of megaprojects in Sri Lanka. The findings reveal transitional challenges and appropriate feasible solutions for EDMS adaptation. This can be applied to the cost management of megaprojects in other developing countries as well.

Published in June 2020, the European Union (EU) Taxonomy Regulation is an important tool for the reorientation of capital flows toward sustainability, establishing a classification system that enables investors to identify green economic activities. Confronted by the reporting demands of this regulation, companies are caught in a sustainability economic revolution. This study seeks primarily to understand firms’ responses to the EU taxonomy, and whether they recognize value creation opportunities by aligning market and nonmarket strategies with the taxonomy goals. For that, we conducted expert interviews and adopted a conceptual framework based on institutional theory, dynamic capabilities view and nonmarket strategy research. Our findings indicate that most firms respond reactively, while firms with sustainability-driven business models tend to respond in an anticipatory way, and firms with high greenhouse gas (GHG) emissions and low taxonomy eligibility in a defensive way. We also find evidence for mimetic isomorphism related to the influence of consulting and auditing services. Further, high levels of uncertainty, ambiguity and lack of clarity has a great impact on firms’ responses and motives. Finally, this study highlights the EU taxonomy considering a paradigmatic shift toward sustainability, which is not recognized by most firms. To this end, we find that most companies have not identified opportunities arising from nonmarket integration and, rather, see the taxonomy only as an extra regulation to be compliant with. Hence, we argue that it is crucial that firms contextualize the taxonomy within its larger institutional paradigmatic shift to capture the importance of going beyond mere compliance.

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies like India.

Around nine growth-accelerating enablers of green financing were found through literature and unstructured interviews and analysed using the total interpretive structural modelling (TISM) method. The hierarchical link between each factor is established using TISM, and further to evaluate the driver-dependent relationship the Matriced’ Impacts Croises Appliquee Aaun Classement (MICMAC) approach is utilised.

The findings demonstrate an interrelationship between growth-accelerating factors, where the political environment and information and communication technology (ICT), have minimal dependency but a strong driving force. Political environment and ICT are found as strategic-level factors lying at the bottom of the model driving towards the dependent variables. The government should focus on enacting effective policies such as the green credit guarantee scheme and carbon credit and establishing a regulatory framework to enhance green financing.

This study examines the literature to generalise the findings and focus on the primary motivators for developing green financing. To increase green financial activity, practitioners must concentrate on aspects with significant driving forces. Furthermore, it makes organisations more profitable, efficient and competitive and promotes long-term growth.

The study is the first in the literature which identifies the growth-accelerating factors of green financing using the TISM and MICMAC-based hierarchical models.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.

This paper studies the interactive valuation discourses of an online user community (transfermarkt.de) that seeks to determine market values for soccer players. Despite their seemingly casual nature, these values have featured in newspapers, transfer negotiations, academic research, and capital market communication – and have thus become reified.

The paper employs netnographic research methodology to collect and thematically analyze a wide range of user entries on the platform. These entries are studied using theoretical insights from the sociology of quantification and valuation.

The analysis reveals how values are constructed in constant interaction between value-proposing users and value-justifying “experts.” This dynamic form of relational valuation positions players relative to one another as well as to actual transactions on the transfer market. In the absence of authoritative guidelines, it is this possibility and affordance for interaction that enacts a coherent valuation regime. The paper further reveals the platform's response to a disruptive event, which risked bringing the user-expert dynamics to a halt, requiring intervention from the platform to repair its valuation frame.

The paper responds to increased scholarly interests in the valuation of professional athletes. It contributes to the extant literature on valuation, first, by analyzing the dynamic valuation work that feeds into the social construction of values and, second, by studying platform participation and user interaction in a socially engineered online space.

This study aims to test the market anomaly of herding behavior driven by the response to supply chain disruptions in extreme market conditions such as those observed during COVID-19. The authors empirically test the response of the capital market participants for B2B firms, resulting in herding behavior.

Using the event study approach based on the market model, the authors test the impact of supply chain disruptions and resultant herding behavior across six sectors and among different B2B firms. The authors used cumulative average abnormal returns (CAAR) and cross-sectional absolute deviation (CSAD) to examine the significance of herding behavior across sectors.

The event study results show a significant effect of COVID-19 due to supply chain disruptions across specific sectors. Herding was detected across the automotive and pharmaceutical sectors. The authors also provide evidence of sector-specific disruption impact and herding behavior based on the black swan event and social learning theory.

The authors examine the impact of COVID-19 on herding in the stock market of an emerging economy due to extreme market conditions. This is one of the first studies analyzing lockdown-driven supply chain disruptions and subsequent sector-specific herding behavior. Investors and regulators should take sector-specific responses that are sophisticated during extreme market conditions, such as a pandemic, and update their responses as the situation unfolds.