Search results

This study aims to assess the effectiveness of a scale measuring artificial intelligence capabilities by using the resource-based theory. It seeks to examine the impact of these capabilities on the organizational-level resources of dynamic capabilities and organizational creativity, ultimately influencing the overall performance of government organizations.

The calibration of artificial intelligence capabilities scale was conducted using a combination of qualitative and quantitative analysis tools. A set of 26 initial items was formed in the qualitative study. In the quantitative study, self-reported data obtained from 344 public managers was used for the purposes of refining and validating the scale. Hypothesis testing is carried out to examine the relationship between theoretical constructs for the purpose of nomological testing.

Results provide empirical evidence that the presence of artificial intelligence capabilities positively and significantly impacts dynamic capabilities, organizational creativity and performance. Dynamic capabilities also found to partially mediate artificial intelligence capabilities relationship with organizational creativity and performance, and organizational creativity partially mediates dynamic capabilities – organizational creativity link.

The application of artificial intelligence holds promise for improving decision-making and problem-solving processes, thereby increasing the perceived value of public service. This can be achieved through the implementation of regulatory frameworks that serve as a blueprint for enhancing value and performance.

There are a limited number of studies on artificial intelligence capabilities conducted in the government sector, and these studies often present conflicting and inconclusive findings. Moreover, these studies indicate literature has not adequately explored the significance of organizational-level complementarity resources in facilitating the development of unique capabilities within government organizations. This paper presents a framework that can be used by government organizations to assess their artificial intelligence capabilities-organizational performance relation, drawing on the resource-based theory.

Grounded in dynamic capabilities theory, this study aims to examine how dynamic capabilities and a transactive memory system (TMS) can build the resilience of service organizations and improve their financial performance. Limited studies examine the link between a TMS and organizational resilience.

The authors test a theoretical model on a sample of 350 UK service firms that were impacted by the COVID-19 pandemic and analyze the data using partial least square structural equation modeling.

Results highlight the positive effects of a TMS and dynamic capabilities on organizational resilience. Only a TMS and organizational resilience have direct positive effects on financial performance.

To the best of the authors’ knowledge, this is the first study to ascertain the influence of a TMS on organizational resilience in service firms following adversity.

This study aims to explore how to overcome and address the loss of exploratory innovation, thereby achieving greater success in exploratory innovation. This phenomenon of loss occurs when enterprises decrease their investment in and engagement with exploratory innovation, ultimately leading to an insufficient amount of such innovation efforts. Drawing on dynamic capabilities, this study investigates the relationship between organizational foresight and exploratory innovation and examines the moderating role of breakthrough orientation/financial orientation.

This study used survey data collected from 296 Chinese high-tech companies in multiple industries and sectors.

The evidence produced by this study reveals that three elements of organizational foresight (i.e. environmental scanning capabilities, strategic selection capabilities and integrating capabilities) positively influence exploratory innovation. Furthermore, this positive effect is strengthened in the context of a high-breakthrough orientation. Moreover, the relationships among environmental scanning capabilities, strategic selection capabilities and exploratory innovation become weaker as an enterprise’s financial orientation increases, whereas a strong financial orientation does not affect the relationship between integrating capabilities and exploratory innovation.

Ambidexterity is key to successful enterprise innovation. Compared with exploitative innovation, it is by no means easy to engage in exploratory innovation, which is especially important in high-tech companies. While the loss of exploratory innovation has been observed, few empirical studies have explored ways to promote exploratory innovation more effectively. A key research implication of this study pertains to the role of organizational foresight in the improvement of exploratory innovation in the context of high-tech companies.

This paper contributes to the broader literature on exploratory innovation and organizational foresight and provides practical guidance for high-tech companies regarding ways of avoiding the loss of exploratory innovation and becoming more successful at exploratory innovation.

The purpose of this paper is to provide a dynamic, multi-faceted and multi-temporal model of organizational change capability (OCC) to better grasp the complexity of this construct which is still mainly defined through its facilitating conditions rather than its own characteristics.

Building on the literature on organizational learning, punctuated equilibrium, continuous transformation, organizational ambidexterity and dynamic capabilities, this paper critically analyzes the OCC construct by challenging the ways it is currently studied.

This paper highlights that OCC contains five dynamically and temporally interrelated dimensions: learning from past change experience, managing continuous change, managing episodic change, managing change without compromising core organizational activities as well as anticipating future change. A set of propositions that link the construct to its facilitators and outcomes are also suggested.

This conceptual analysis shows that recognizing the existence of tensions in change management constructs is crucial to gaining a deeper understanding of the complexities that organizations are facing today. In addition, by proposing a model both in continuity with the literature by adopting a dynamic conception of OCC, but also in discontinuity by shifting the focal point of analysis towards the essence of the construct rather than its peripheral variables, this research takes a step forward to tackle the remaining misconceptions around the interpretation of change capability.

This study aims to propose a multi-level (bottom-up) analysis to build an organizational change capability (OCC) development model by integrating paradox and social cognitive theories. Using these theories, OCC (Level 2) is influenced by the leader’s paradox mindset (Level 1) and collective PsyCap (Level 2). The study also examined the moderating effect of magnitude to change on the effect of leader’s paradox mindset on OCC.

The proposed hypotheses were tested empirically using data from 327 respondents and 48 work teams from 21 leading private higher education institutions in Indonesia. To analyze the data, a multi-level analysis was conducted with Mplus software.

The results showed that, in a cross-level relationship, leader’s paradox mindset had a positive effect on OCC, whereas OCC mediated the effect of leader’s paradox mindset on organizational change performance. On an organizational level, collective PsyCap affected OCC, and OCC significantly mediated the relationship between collective PsyCap and organizational change performance. Moreover, the authors found a moderating effect of magnitude on change of leader’s paradox mindset to OCC.

This study used a multi-level analysis to evaluate the mechanisms of influence of leader’s paradox mindset (bottom-up) on OCC and the moderation effect of magnitude to change in an Indonesian context.

The rise of emerging economies in the innovation landscape has often been attributed to the positive spillovers of innovation capabilities from multinational corporations (MNCs). However, it is less certain that their innovative capabilities imported from the home country function effectively in the host country from the outset. This study examines the performance of the innovation capabilities of MNC subsidiaries in emerging economies over time by considering the gradual process of their learning about host countries.

We employed stochastic frontier analysis to measure innovation capabilities, our focal construct. For regression analysis, we applied the Mundlak estimator, a variant of the fixed-effects panel estimator, to a sample comprising subsidiaries of MNCs from technologically advanced nations operating in Korea between 2006 and 2016.

Our results indicate that the innovation capabilities of MNC subsidiaries initially underperform those of local firms but improve over time, eventually surpassing the capabilities of their local counterparts. Furthermore, our findings reveal that institutional distance amplifies the underperformance of the innovation capabilities of MNC subsidiaries.

This study contributes to the literature by extending both theoretical development and empirical measurement of innovation capabilities in cross-national settings. Additionally, it deepens our understanding of whether and how MNC subsidiaries adapt their innovation capabilities to the local market environment.

The effect of dynamic capabilities on operational excellence and the moderating effect of environmental dynamism on the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka were investigated while developing new psychometric scales to assess operational excellence and dynamic capacities constructs.

We followed the exploratory sequential research design with a mixed-method research approach, aligning with the pragmatic research philosophy. Thus, both qualitative and quantitative research methods were followed.

Dynamic capabilities positively affect operational excellence, and environmental dynamism moderates the relationship between operational excellence and dynamic capabilities in the apparel industry in Sri Lanka such that when a higher environmental dynamism exists, a weaker positive relationship exists between dynamic capabilities and operational excellence. The two main dimensions of the operational excellence construct are continuous improvement of sustainable operational performance and sustainable competitive advantages. It empirically confirmed that sensing, seizing and reconfiguring capabilities are the three main dimensions of the dynamic capabilities construct.

This study was limited to the apparel industry in Sri Lanka. This research phenomenon should be explored in other industrial sectors worldwide to generalize the findings. The practitioners in the apparel sector may improve the organizational dynamic capabilities to achieve operational excellence and keep a strong positive relationship between dynamic capabilities and operational excellence in a highly dynamic environment if they address out-of-family situations with out-of-the-box thinking.

We generated two new empirical findings: (1) dynamic capabilities positively affect operational excellence, and (2) environmental dynamism moderates the relationship between dynamic capabilities and operational excellence. Also, we introduced validated new scales for assessing operational excellence and dynamic capabilities.

Given the important role of change capability for organizational development and competitive advantage, the purpose of this study is to clarify the influences of transformational leadership (TL) on organizational change capability (OCC) via mediating roles of two specific aspects of trust in leadership namely disclosure-based trust and reliance-based trust.

Structural equation modeling is applied to test the degree of influences of TL and employee trust on OCC via empirical data collected from 376 participants in 115 small and medium firms in China.

The results show the positive and significant impacts of TL and aspects of employee trust in leadership on OCC. It indicated that disclosure-based trust in leadership has a greater influence on change capability in comparison with the effect of reliance-based trust in leadership. Especially, the findings have shown the evidence supporting the mediating mechanism of aspects of employee trust in leadership between TL and OCC.

This study provides the practical initiatives that highlight the importance of applying TL style to build and improve the trust of employees in their leadership for fostering OCC.

The paper has significantly advanced and deepened insight of how transformational leaders nurture employee’s specific shades of trust in leadership for fostering OCC. The valuable findings of this study contribute to enriching the theoretical basis of organizational behavior and change management, and can be used to analyze and explain the relationships between TL, employee’s trust in leadership and organizational capability for change.

This study aimed to examine the role of big data analytics capabilities (BDAC) in fostering organizational innovation capabilities and, consequently, in achieving economic, social and environmental sustainability.

Through the lens of dynamic capability theory, this study surveyed 115 hotels using purposive sampling to gain in-depth insights regarding the factors affecting organizational sustainability in the hospitality industry. The data analysis was conducted using partial least squares-structural equation modeling (PLS-SEM).

The findings reported a substantial impact of seven core dimensions (i.e. technology, data, basic resources, technological skills, managerial skills, organizational learning and data-driven culture) in building BDAC among hotels. Moreover, BDAC was also revealed to significantly influence innovation capabilities, positively impacting all three sorts of sustainability performance. Innovation capability also mediated the relationship between BDAC and all sustainability factors.

The findings will assist policymakers and practitioners in developing effective initiatives to enhance the adoption and implementation of data science and technologies, substantially contributing to the “National IR 4.0 Policy” and “Malaysia Digital Economy Blueprint” and achieving sustainable development goals (SDGs).

The originality of this study is established by investigating the interplay between BDAC, innovation capability and sustainability performance, particularly in the context of the hotel industry, whereas the existing studies focus on exploring the advantages of BDA.

Although businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.

The integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.

The results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.

In pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.

The provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.

While previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.