Journal of Enterprise Information Management最新文献

Purpose

This study aims to investigate the relationship between strategy intent (product-service innovation intention) and outcome (product-service innovation outcome), and the role that external sources of innovation play in influencing this relationship.

Design/methodology/approach

Using data obtained from the community innovation survey, we apply a logit regression to a sample of 1,419 Portuguese firms. By examining the moderating effect of open innovation breadth, we assess how the relationship between differentiation intent and outcome is contingent upon the involvement of external stakeholders.

Findings

Our findings reveal that the relationship between differentiation intent and outcome is contingent upon the moderating effect of open innovation breadth. Our analysis suggests that the negative influence of different sources of innovation can be addressed by adopting a paradox lens.

Practical implications

This research provides valuable insights for managers. By simultaneously pursuing a differentiation strategy and engaging in collaboration with external sources, firms may compromise their ability to effectively differentiate their offer. Managers should consider the potential tensions arising from internal and external stakeholder relationships to optimize their innovation strategies.

Originality/value

This study contributes to the existing literature by shedding light on the role of external innovation sources in influencing the relationship between differentiation intent and outcome and the importance that information systems may have in this relationship. By exploring the moderating effect of open innovation breadth, we provide a nuanced understanding of how firms can navigate organizational tensions and leverage innovation for competitive advantage.

Purpose

This study aims to explore the key challenges and drawbacks of smart contracts (SCs) and how they impact digital resilience within small and medium enterprises (SMEs). Whilst this type of technology is seen as a step forward in terms of traceability, transparency and immutability to increase digital resilience, we argue that it should be approached with trepidation.

Design/methodology/approach

In developing this paper, the authors conduct a systematic literature search using the Scopus database. Through this, we identified 931 relevant articles, of which 30 were used as the focus of this article. Thematic analysis was used as the analytical approach to develop themes and meaning from the data.

Findings

In this paper, there is an emphasis on the importance of understanding the potential risks associated with SC implementation, as well as identifying appropriate strategies for mitigating any negative impact. In our findings, we puts forward three key themes, namely legality, security and human error, which we argue are key smart contract challenges that impact SME digital resilience.

Originality/value

In this paper, we propose the notion of “centralised control in decentralised solutions”. This comes from the research highlighting SC weaknesses in digital resilience for SMEs. We argue that there is a need for standards, regulations and legislation to address these issues, advocating, ironically, a centralised approach to decentralised technology.

Purpose

Machine learning (ML) analytical tools are increasingly being considered as an alternative quantitative methodology in management research. This paper proposes a new approach for uncovering the antecedents behind product and product–service innovation (PSI).

Design/methodology/approach

The ML approach is novel in the field of innovation antecedents at the country level. A sample of the Equatorian National Survey on Technology and Innovation, consisting of more than 6,000 firms, is used to rank the antecedents of innovation.

Findings

The analysis reveals that the antecedents of product and PSI are distinct, yet rooted in the principles of open innovation and competitive priorities.

Research limitations/implications

The analysis is based on a sample of Equatorian firms with the objective of showing how ML techniques are suitable for testing the antecedents of innovation in any other context.

Originality/value

The novel ML approach, in contrast to traditional quantitative analysis of the topic, can consider the full set of antecedent interactions to each of the innovations analyzed.

Purpose

In the reduction of food waste and the provision of food to the hungry, food banks play critical roles. However, as they are generally run by charitable organisations that are chronically short of human and other resources, their inbound logistics efforts commonly experience difficulties in two key areas: 1) how to organise stocks of donated food, and 2) how to assess the donated items quality and fitness for purpose. To address both these problems, the authors aimed to develop a novel artificial intelligence (AI)-based approach to food quality and warehousing management in food banks.

Design/methodology/approach

For diagnosing the quality of donated food items, the authors designed a convolutional neural network (CNN); and to ascertain how best to arrange such items within food banks' available space, reinforcement learning was used.

Findings

Testing of the proposed innovative CNN demonstrated its ability to provide consistent, accurate assessments of the quality of five species of donated fruit. The reinforcement-learning approach, as well as being capable of devising effective storage schemes for donated food, required fewer computational resources that some other approaches that have been proposed.

Research limitations/implications

Viewed through the lens of expectation-confirmation theory, which the authors found useful as a framework for research of this kind, the proposed AI-based inbound-logistics techniques exceeded normal expectations and achieved positive disconfirmation.

Practical implications

As well as enabling machines to learn how inbound logistics are handed by human operators, this pioneering study showed that such machines could achieve excellent performance: i.e., that the consistency provided by AI operations could in future dramatically enhance such logistics' quality, in the specific case of food banks.

Originality/value

This paper’s AI-based inbound-logistics approach differs considerably from others, and was found able to effectively manage both food-quality assessments and food-storage decisions more rapidly than its counterparts.

Purpose

The global prevalence of social media and its potential to cause polarization are highly debated and impactful. The previous literature often assumes that the ideological bias of any media outlet remains static and exogenous to the polarization process. By studying polarization as a whole from an ecosystem approach, the authors aim to identify policies and strategies that can help mitigate the adverse effects of polarization and promote healthier online discourse.

Design/methodology/approach

To investigate online polarization, the authors perform a systematic review and analysis of approximately 400 research articles to explore the connection between cognitive bias and polarization, examining both causal and correlational evidence. The authors extensively evaluate and integrate existing research related to the correlation between online polarization and crucial factors such as public engagement, selective exposure and political democracy. From doing so, the authors then develop a PolarSphere ecosystem that captures and illustrates the process of online polarization formation.

Findings

The authors' review uncovers a wide range of associations, including ideological cognition, bias, public participation, misinformation and miscommunication, political democracy, echo chambers and selective exposure, heterogeneity and trust. Although the impact of bias on social media polarization depends on specific environments and internal/external conditions, certain variables exhibit strong associations across multiple contexts. The authors use these observations as a basis from which to construct PolarSphere, an ecosystem of bias-based polarization on social media, to theorize the process of polarization formation.

Originality/value

Based on the PolarSphere ecosystem, the authors argue that it is crucial for governments and civil societies to maintain vigilance and invest in further research to gain a deep comprehension of how cognitive bias affects online polarization, which could lead to ways to eliminate polarization.

Purpose

In a fast-paced and hypercompetitive environment, organizational members are awash with paradoxes where they are forced to accomplish opposing goals simultaneously (“both/and”) instead of choosing one over the other (“either/or”). The literature has acknowledged paradox as a common type of contradiction in managing information and information technology (IT), but few studies have investigated how individuals can leverage paradoxical tensions. Drawing upon paradox theory, this study develops a research model that embodies a “both/and” paradigm in paradoxical tensions via analytical alignment, a paradox mindset and resilience under environmental dynamism.

Design/methodology/approach

This study examines the research model using hierarchical regression analysis with 308 analytics experts.

Findings

Empirical results find that the alignment of analytical technology and data-driven culture (AT-2DC) has a positive effect on a paradox mindset. Results also show that a paradox mindset has a positive influence on resilience. AT-2DC alignment also mediates the relationship between paradox mindset and resilience. In addition, AT-2DC alignment is more critical to a paradox mindset under a high level of environmental dynamism.

Originality/value

This study sheds light on how individuals can leverage paradoxical tensions with a “both/and” perspective and stay resilient when managing opposing demands and changes.

Purpose

The purpose of this paper is to provide an integrative picture of the state of the art of the literature on digitalisation of small and medium-sized enterprises (SMEs) as an enabler for their internationalisation process and as a comprehensive view of the specific domains impacted by digital technologies as well as their repercussions on the international outreach.

Design/methodology/approach

A systematic review which leverages a descriptive analysis of extant literature and an axial coding technique has been conducted to shed light on the current knowledge and to identify primary research areas and future research lines.

Findings

The research indicates that digitalisation impacts the internationalisation of SMEs in three specific domains: (1) internationalisation through the adoption of information and communication technologies (ICT) technologies and e-commerce platforms; (2) international expansion through the digitalisation of value chain activities and (3) international outreach through knowledge acquisition on digital platforms.

Originality/value

The value of this study is threefold. First, the authors attempt to systematically review the literature on SMEs digitalisation and internationalisation and provide a holistic perspective on the intertwining of these two research streams. Second, the authors propose a novel conceptualisation on the dimensions of SMEs digitalisation as enablers to internationalisation. Third, the authors put forward promising future lines of research.

Highlights

1. Digitalisation represents a pivotal strategy that allows companies to build new strategic capabilities and is a propeller for SMEs internationalisation.

2. Through e-commerce, SMEs could compete at the same level of multinational companies but enduring lower costs of expansion.

3. Digital platforms allow SMEs to enhance the learning processes about international markets through an immediate access to relevant information.

4. Digital entrepreneurship has enabled SMEs to develop new configurations of value chain activities, evolving their business model or reaching new markets.

5. SMEs are changing the “business as usual” paradigm offering digital tools to build modular architectures that are scalable and agile in their evolution ability.

Purpose

This study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.

Design/methodology/approach

The design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.

Findings

The results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.

Originality/value

This study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.