Search results

Digital technologies promise efficiency gains and untapped opportunity. Adoptions of digital technology lead firms to rethink their organizational setup and existing practices. This paper aims to present a management innovation-based framework that describes new processes and practices for digital transformation.

This study uses a structural equation modeling approach to test the framework with survey responses from a sample of 901 Taiwanese organizations – both local firms and multinational subsidiaries – to explore the linkages between adoption of digital technologies and digital maturity.

The results reveal that management innovation mediates the relationship between digital technology adoption and digital maturity. Moreover, fast-paced environments have a greater impact of management innovation toward digital maturity than slow-paced environments.

This study adds to emerging research that considers the role of organizational learning in digital transformation efforts. The extent to which organizations link the lessons from direct experience to digital routines through which management innovation is implemented determines to a large extent whether this strategic initiative is optimized by the firm. More generally, the findings point to the mutual importance of digital maturity and experiential learning efforts, and suggest a specific means by which learning processes are mobilized by innovating organizations. This study contributes to digital transformation research by providing insight into how a firm can restart failed transformation initiatives of this kind.

This study aims to examine the impact of digital transformation on firms’ value and explore the mediating impact of ESG performance and moderating impact of information interaction.

Data was collected from companies listed on the Shanghai and Shenzhen stock exchange between 2012 and 2020 with 21,488 observational samples, featuring a selection of 3,348 companies. Panel data regression techniques were used to test the mediating role of ESG performance and the moderating role of information interaction.

The study found that digital transformation can improve firms’ ESG performance, which in turn positively affects their value. The firms that engage in more interaction with outsiders benefit more from digital transformation and have a higher value.

This study provides new theoretical insight into improving firms’ value through digital transformation and ESG performance. It is the first to discuss and study the moderating role of information interaction in the relationship between digital transformation and firms’ value.

Wind power is the most promising renewable energy source in China. The development of digital technologies has brought about unprecedented growth opportunities and prospects for wind power. However, the relationship between digital technology adoption and total factor productivity (TFP) in the wind power industry in China has not been empirically assessed. This study aims to clarify whether and how digital technology adoption affects the TFP of the wind power industry in China.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study proposes and verifies relevant hypotheses with two-way fixed effects regression models.

The empirical results indicate that digital technology adoption is the cornerstone of the TFP of China’s wind power industry. Reconfiguration capability and technological innovation serially mediate the above relationship. In addition, the incentive effect of digital technology adoption varies among wind power firms. The impact of digital technology adoption is more significant in firms that are old and located in economically undeveloped regions.

This study is one of the earliest attempts to investigate the relationship between digital technology adoption and TFP in the renewable energy sectors of emerging economies. By integrating dynamic capability theory and the analytical framework of “Capability-Behavior-Performance” into the digital context, this study offers the theoretical insights into how digital technology adoption can enhance organizational reconfiguration capability, thereby stimulating technological innovation and subsequent TFP. Additionally, the impacts of different digital technologies are estimated in entirety, rather than in isolation.

Firms in emerging economies are generally at a disadvantage in terms of resources, which may limit their digital transformation. The Chinese government has designed and promulgated a series of wind power policies from the perspectives of support and regulation. The former provides scarce resources for enterprises and thus alleviating financial constraints. While the latter increases the demands for advanced technologies, thereby triggering resource bricolages. This study aims to clarify the impact of industrial policy on the digital transformation of the Chinese wind power industry, and the role of financing constraint and resource bricolage in the above relationship.

Based on the data of listed companies in the Chinese wind power industry from 2006 to 2021, this study clarifies the impact and mechanism of industrial policy on firm digital transformation with fixed effect regression models.

Empirical results indicate that both supportive and regulatory policies are the cornerstone of the digital transformation of the Chinese wind power industry. Financial constraint and resource bricolage, respectively, mediate the impact of supportive and regulatory policies. However, the mix of supportive and regulatory policies inhibits digital transformation. Moreover, industrial policies are more effective for the digital transformation of state-owned enterprises, as well as enterprises in economically underdeveloped regions.

This study investigates the path of government intervention driving firm digital transformation from the resource-related perspective (i.e. financial constraint and resource bricolage), and its analytical framework can be extended based on other theories. The combined effects of cross-sectoral policies (e.g. wind power policy and digital infrastructure policy) can be further assessed. The marginal net benefit of government intervention can be calculated to determine whether it is worthwhile.

This study emphasizes the necessity of government intervention in the digital transformation of enterprises in emerging economies. The governments should align the policy targets, clarify policy recipients and modify policy process of different categories of industrial policies to optimize the effectiveness of policy mix. Given that the effectiveness of government intervention varies among different categories of enterprises, the competent agencies should design and promulgate differentiated industrial policies based on the heterogeneity of firms to improve the effectiveness and efficiency of industrial policies.

This is one of the earliest explorations of industrial policies’ effect on the digital transformation of the renewable energy sector in emerging economies, providing new evidence for institutional theory. Meanwhile, this study introduces financial constraint and resource bricolage into the research framework and attempts to uncover the mechanism of industrial policy driving the digital transformation of enterprises in emerging economies. Besides, to expand the understanding of the complex industrial policy system, this study assesses the effectiveness of the industrial policy mix.

This research intends to analyze the innovation ecosystem factors that play a vital role in firm performance. As a result, large-scale empirical studies on the innovation ecosystem are rare, and fewer efforts have been made to determine if and how different factors affect the ecosystem models of firms. There has yet to be a substantial empirical study on the innovation ecosystem.

Data were acquired from Pakistani IT companies. The results show that factors of the innovation ecosystem significantly contribute to business performance. The essential assumption is that resource endowment, organizational culture, knowledge and competence, and technology capability are allied to the innovation ecosystem.

The findings are crucial from a managerial view because firms must focus on changing their innovation ecosystem factors model to achieve greater performance. Radical changes in the firms will only be worthwhile if they value their resource endowments. To attain superior firm performance via influential factors of the innovation ecosystem, IT administrators need to build organizational cultural capacities to adapt to changes brought on by digitization quickly and effectively. However, this must be supplemented by improving organizational knowledge, competencies and technological capabilities to enable organizations to modify their ecosystems.

Eventually, firms can better respond to changes in their settings if they combine these variables by implementing an effective innovation ecosystem model, which leads to greater sector and superior financial performance.

Intent detection (ID) and slot filling (SF) are two important tasks in natural language understanding. ID is to identify the main intent of a paragraph of text. The goal of SF is to extract the information that is important to the intent from the input sentence. However, most of the existing methods use sentence-level intention recognition, which has the risk of error propagation, and the relationship between intention recognition and SF is not explicitly modeled. Aiming at this problem, this paper proposes a collaborative model of ID and SF for intelligent spoken language understanding called ID-SF-Fusion.

ID-SF-Fusion uses Bidirectional Encoder Representation from Transformers (BERT) and Bidirectional Long Short-Term Memory (BiLSTM) to extract effective word embedding and context vectors containing the whole sentence information respectively. Fusion layer is used to provide intent–slot fusion information for SF task. In this way, the relationship between ID and SF task is fully explicitly modeled. This layer takes the result of ID and slot context vectors as input to obtain the fusion information which contains both ID result and slot information. Meanwhile, to further reduce error propagation, we use word-level ID for the ID-SF-Fusion model. Finally, two tasks of ID and SF are realized by joint optimization training.

We conducted experiments on two public datasets, Airline Travel Information Systems (ATIS) and Snips. The results show that the Intent ACC score and Slot F1 score of ID-SF-Fusion on ATIS and Snips are 98.0 per cent and 95.8 per cent, respectively, and the two indicators on Snips dataset are 98.6 per cent and 96.7 per cent, respectively. These models are superior to slot-gated, SF-ID NetWork, stack-Prop and other models. In addition, ablation experiments were performed to further analyze and discuss the proposed model.

This paper uses word-level intent recognition and introduces intent information into the SF process, which is a significant improvement on both data sets.

Choosing the proper selling format for online retail has long been a critical issue for many platforms to consider, whereas the emergence and popularity of live-streaming have had a massive impact on the platform's business. As a result, selecting the suitable operating strategy for the live channel has become another critical issue for platforms. In such a context, what will be the impact of live-streaming on selling formats?

In order to explore these issues, we identified two selling formats (wholesale reselling or agency selling) as well as two operating strategies (introduce or discard). Thereby, four channel-structures are constructed, namely the reselling-discard model (WN), the reselling-introduce model (WL), the agency-discard model (AN), and the agency-introduce model (AL). We comprehensively compare how different structures affect stakeholders' interests, consumer surplus, and social welfare through equilibrium analyses.

These results help clarify the impact of critical factors (e.g. self-effort attribute, cross-effort attribute, and commission ratio) on the choice of models. We find that regardless of the selling agreement between the manufacturer and the platform, the introduction of a live store is necessary; specifically, when the commission ratio is high, the platform's optimal decision is first to sign an agency agreement and then apply live selling (AL); conversely, when the commission ratio is low, the platform's optimal strategy is first to enable the live channel and then to select the reselling format (WL), together, this also reveals, from a theoretical perspective.

Our study includes the dual analysis of selling formats and channel operations, considering the inherent dual attributes of service efforts and the external competitive environment.

This paper investigates the dual interactive effects of manufacturer encroachment on the supply chain and retailer provision of retail services.

Consider a supply chain dominated by manufacturers, retailers, and e-commerce platforms, with the manufacturers selling the same product online and offline. Utilizing Stackelberg’s game theory, examples of wholesale and retail prices and profits of participants in the supply chain under different channels are analyzed. An effective encroachment strategy for manufacturers facing different retail service investment strategies of traditional retailers is given.

When traditional retailers do not invest in retail services, they will lose more profit due to competition with the manufacturer. At this time, the retailer does not want the manufacturer to encroach. The traditional retailer’s investment in retail services will enhance its and the manufacturer’s profits, incentivizing the manufacturer to pursue an aggressive expansion strategy.

(1) Considers a situation where the selling efficiency of the manufacturer is lower than that of the traditional retailer. (2) The interaction between traditional retailers’ retail service investment strategies and manufacturers’ encroachment strategies is investigated where the manufacturer is the dominant player. The three modes of online direct sales, resale, and third-party platform agency are compared to provide a basis for decision-making on different types of manufacturers’ encroachment. (3) Offline retail services not only directly increase sales in the offline market but also indirectly have a negative effect on the online market.

The rapid development and widespread application of artificial intelligence tools have raised concerns about how designers are embracing these technologies. This study investigates the factors influencing designers' behavioral intention to use and disclose the use of generative artificial intelligence.

A quantitative research approach was employed, designing a structured questionnaire based on Self-Determination Theory to assess the impact of various psychological and social dimensions. The questionnaire included dimensions such as autonomy, competence, relatedness, social influence, value fit and social innovativeness. A Partial Least Squares Structural Equation Modeling analysis was conducted on 309 valid responses from diverse design fields.

Competence and relatedness are significant factors influencing designers' continuance intention to use generative artificial intelligence. Although autonomy does not significantly affect continuance intention, it plays a crucial role in the decision to disclose artificial intelligence participation. Social influence and value fit significantly shape autonomy, competence and relatedness, while the impact of social innovativeness is relatively limited.

This study clarifies the factors influencing designers' continuance intention and disclosure of generative artificial intelligence tools from both individual and social dimensions, enhancing the understanding of the relationship between designers and generative artificial intelligence tools. It provides valuable insights for the development of artificial intelligence technology and the future trends in the design industry, offering significant theoretical and practical value.

Although the literature recognizes that coopetition plays a significant role in the success of international construction joint ventures (ICJVs), the impacts of coopetition on the performance outcomes of ICJVs remain largely unknown. This study extends this line of research by theorizing coopetition from three dimensions, i.e. coopetition intensity, coopetition balance and coopetition structure, and examining the relationships between coopetition and ICJV performance outcomes from both the contingency and configuration perspectives.

The hypotheses were tested using survey data from a sample of 188 ICJVs. Structural equation modelling was employed for the contingency approach to estimate the relationships between the three dimensions of coopetition and performance. For the configuration approach, cluster analysis was utilized to identify coopetition patterns. Subsequently, an analysis of variance was employed to analyse the relationships between these coopetition patterns and performance.

The contingency results indicate that while coopetition intensity is positively related to all types of performance, coopetition balance is only positively related to project performance and partner performance. Moreover, coopetition structure is only related to partner performance and socioenvironmental performance. The configuration approach identifies six patterns of coopetition, manifesting different levels of project, partner and socioenvironmental performance.

These findings, therefore, contribute to the ICJV literature by extending the understanding of how coopetition dimensions individually and jointly influence ICJV performance.