Search results

Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search.

Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research.

This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies.

This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

This study is exploratory in nature and designed to address poorly documented issues in the literature. The dimensions of regional distribution or spatial organisation of Industry 4.0 (I4.0), including the potential role of clusters, have only recently been addressed, with most available studies focusing on advanced, mainly Western European countries. Although developing fast, the literature on I4.0 in other countries, such as the Central and Eastern European or post-transition economies like Poland, needs to pay more attention to the spatial distribution or geographical and organisational aspects. In response to the identified knowledge gap, this paper aims to identify the role of clusters in the transformation towards I4.0. This explains why clusters may matter for advancing the fourth digital transformation, how advanced in implementing I4.0 solutions are the residents of Polish clusters and how they perceive the advantages of cluster membership for such implementation. Finally, it seeks to formulate policy recommendations based on the evidence gathered.

The methodology used in this study combines quantitative analysis of secondary data from a cluster benchmarking survey with a case study approach. The benchmarking survey, conducted by the polish agency for enterprise development in 2021, gathered responses from 435 cluster members and 41 cluster managers, representing an estimated 57% of the current clusters in Poland. In addition to quantitative analysis, a case study approach was used, incorporating primary sources such as interview with cluster managers and surveys of cluster members, as well as secondary sources like company documents and information from cluster organisation websites. Statistical analysis involved assessing the relationship between technology implementation and the adoption of management systems, as well as exploring potential correlations between technology use and company characteristics such as revenue, export revenue share and number of employees using Pearson correlation coefficient.

In Poland, implementing I4.0 technologies by cluster companies is still modest. The cluster has influenced the use of I4.0 technologies in 23% of surveyed companies. Every second surveyed company declared a positive impact of a cluster on technological advancement. The use of I4.0 technologies is not correlated with the revenue of clustered companies. A rather bleak picture emerges from the results, revealing a need for more interest among cluster members in advancing I4.0 technologies. This may be due to a comfortable situation in which firms still enjoy alternative competitive advantages that do not force them to seek new advanced advantages brought about by I4.0. It also reflects the sober approach and awareness of associated high costs and necessary investments, which are paramount and prevent successful I4.0 implementation.

The limitations inherent in this study reflect the scarcity of the available data. This paper draws on the elementary survey administered centrally and is confined by the type of questions asked. The empirical section focuses on an important, though only one selected sector of the economy – the automotive industry. Nevertheless, the diagnosis of the Polish cluster’s role in advancing I4.0 should complement the existing literature.

The exploratory study concludes with policy recommendations and sets the stage for more detailed studies. Amidst the research’s limitations, this study pioneers a path for future comprehensive investigations, enabling a deeper understanding of Polish clusters’ maturity in I4.0 adoption. By comparing the authors’ analysis of the Polish Automotive Group (PGM) cluster with existing literature, the authors uncover a distinct disparity between the theoretical prominence of cluster catalysis and the current Polish reality. Future detailed dedicated enquiries will address these constraints and provide a more comprehensive map of Polish clusters’ I4.0 maturity.

This study identifies patterns of I4.0 implementation and diagnoses the role of clusters in the transformation towards I4.0. It investigates how advanced is the adoption of I4.0 solutions among the residents of Polish clusters and how they perceive the advantages of cluster membership for such transformation. Special attention was paid to the analysis of the automotive sector. Comparing the conclusions drawn from the analysis of the Polish PGM cluster in this case study to those from the literature on the subject, it becomes clear that the catalytic role of clusters in the implementation of I4.0 technologies by enterprises, as emphasised in the literature, is not yet fully reflected in the Polish reality.

This study has conducted exploratory research to understand who should comprise the members of a resilient supply chain for promoting an entrepreneurial ecosystem of a startup project and to determine the mechanisms for the balanced coexistence of all stakeholders. This is necessary to ensure mutual benefits for all stakeholders, each of whom has multidimensional interests. Additionally, this supply chain must be able to withstand any potential disruption risks.

This research has employed a mixed-design approach. In this context, the study conducted an extensive qualitative and quantitative investigation, including 30 interviews and a survey involving 180 potential stakeholders in this supply network, respectively in the capital city of Bangladesh, Dhaka. The analysis of the interviews utilized principles of matrix thinking, while structural equation modeling (SEM) through LISREL was employed to understand cause-and-effect relationships.

Network, platform and governance—these three independent constructs have the potential to contribute to the dependent construct, a resilient supply chain, aimed at promoting an entrepreneurial ecosystem for startup projects. It has been revealed that the management of such projects depends on the rules and regulations within the ecosystem. An excellent governance mechanism is essential for this purpose. To facilitate coexistence, the establishment of a platform is crucial, where cooperation among all members is mandatory.

For practitioners, three distinctive but closely interdependent issues are explored and resolved in this philanthropic study. It has unfolded the elements of any startup project with essential settings.

The identification of the structural dynamics of potential stakeholders within the entrepreneurial ecosystem of startups is largely absent in existing literature. Therefore, there is a need to comprehensively investigate the entire network, including their roles, responsibilities and associations. This study makes a significant and novel contribution to the existing literature. Academics and practitioners alike have ample opportunities to learn from this new aspect of relationships across three distinct areas: the entrepreneurial ecosystem, startup projects and the development of a resilient supply chain.

This research study aims to inquire into the technostress phenomenon at an organizational level from machine learning (ML) and artificial intelligence (AI) deployment. The authors investigated the role of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management amongst managers.

The authors applied an exploratory qualitative method and conducted in-depth interviews based on a semi-structured interview questionnaire. Data were collected from 26 subject matter experts. The data transcripts were analyzed using thematic content analysis.

The study results indicated that role ambiguity, job insecurity and the technology environment contributed to technostress because of ML and AI technologies deployment. Complexity, uncertainty, reliability and usefulness were primary technology environment-related stress. The novel integration of ML and AI automation-augmentation interdependence, along with socio-technical systems, could be effectively used for technostress management at the organizational level.

This research study contributed to theoretical discourse regarding the technostress in organizations because of increased ML and AI technologies deployment. This study identified the main techno stressors and contributed critical and novel insights regarding the theorization of coping mechanisms for technostress management in organizations from ML and AI deployment.

The phenomenon of technostress because of ML and AI technologies could have restricting effects on organizational performance. Executives could follow the simultaneous deployment of ML and AI technologies-based automation-augmentation strategy along with socio-technical measures to cope with technostress. Managers could support the technical up-skilling of employees, the realization of ML and AI value, the implementation of technology-driven change management and strategic planning of ML and AI technologies deployment.

This research study was among the first few studies providing critical insights regarding the technostress at the organizational level because of ML and AI deployment. This research study integrated the novel theoretical paradigm of ML and AI automation-augmentation paradox and the socio-technical systems as coping mechanisms for technostress management.

The purpose of this paper is to evaluate the insights of founding entrepreneurs to understand what they consider as motivating factors in their decision to act upon entrepreneurial intentions. Using this information, the entrepreneurial trigger event influence was conceptualized, and a scale developed for use in subsequent testable models.

Qualitative and quantitative techniques were used to construct an instrument that measures the presence and influence of entrepreneurial behavior triggers. The concept of triggering events was explored with 14 founding entrepreneurs. Themes emerged from this enquiry process which informed the development of four primary entrepreneurial triggering events. Over 600 entrepreneurs participated in the study. Exploratory factor analysis was used to identify dimensions of entrepreneurial triggers and was tested using confirmatory factor analysis.

Entrepreneurs perceive that personal fulfillment and job dissatisfaction serve as two significant trigger events which will lead individuals to engage in entrepreneurial behaviors. This research supports theorizing that suggests entrepreneurial trigger events have influence in motivating individuals to act upon entrepreneurial intentions and some trigger events may have more influence toward behavior than others.

This research is subject to multiple limitations. Trigger events were limited to those identified in literature and the interviews. Most entrepreneurs participating in this study were from a limited geographic region. The entrepreneurs in this study reported their triggering event based on their memory which could have been affected by inaccurate recall or memory bias. No attempt has been made to model the comparative effects of the different variables on entrepreneurial outcomes. Finally, the entrepreneurial trigger event instrument did not measure the participant's demographics or psychographics which could have played a role in the influence of reported trigger event.

This study extends previous research that trigger events serve as catalysts for entrepreneurial behavior. Findings support the premise that different types of triggers have different levels of influence as antecedents of entrepreneurial behavior. Specifically, positive, negative, internal and external entrepreneurial triggering events were explicated. The Entrepreneurial Trigger Event Scale created to facilitate this study enables researchers to explore the effects of types and perceived influences of precipitating trigger events on the intentions of the individual that result in entrepreneurial behavior. The optimized instrument further expanded Shapero's (1975) proposed theory of the origins of entrepreneurial behavior.

The development of a scale provides researchers with the opportunity to include the influence of entrepreneurial trigger events, as perceived by entrepreneurs, in future testable models. Entrepreneurial development organizations can use the knowledge to assist in understanding when potential entrepreneurs may act upon entrepreneurial intentions. Information gained can have significant implications for understanding the initiation of entrepreneurial behavior, entity establishment and business growth.

This research responds to a call for investigation into the influence of entrepreneurial trigger events on a person's decision to act upon entrepreneurial intentions. It is an early attempt to conceptualize a relevant construct of entrepreneurial trigger event influence and to develop a scale for use in empirical testing. It is distinguished by using planned behaviors, push and pull, motivation and drive reduction theories. These theories are applied to the perceptions of successful entrepreneurs to develop a construct and validate it.

This study examined the determinants of mobile health (M-Health) application, adoption, usage and discontinuation among corporate workers diagnosed with hypertension and diabetes in Ghana.

The diffusion innovation and reasoned action theories were employed using an exploratory design. Three hundred corporate workers diagnosed with diabetes and hypertension from three health facilities for the past six months were sampled for the study using a multi-stage sampling technique and administered questionnaires. Descriptive statistics and logistic regression tools were employed in the analysis of data.

The study found a significant number of factors influencing m-health applications adoption, usage and discontinuity. These factors include nature and demand of job, perceived advantage, compatibility, complexity, triability, aesthetics and trust. Aesthetics emerged as the strongest predictive factor for the adoption, usage and discontinuity of use among diabetic and hypertensive corporate workers. With the adoption of M-Health applications, compatibility, as well as nature and demand of job, were significant predictors. With the usage of M-Health applications, complexity, triability, aesthetics and trust were significant predictors. Moreover, perceived advantage, compatibility, complexity and triability influenced significantly the choice to discontinue using M-Health applications. The study concluded that M-Health application functionalities play a valuable role in patients’ intention to adopt, use and discontinue the use of an M-Health application in Ghana.

This exploratory study offers in-depth insight into how major M-Health application features affect its adoption, usage and discontinuity, providing crucial information for future research and the improvement of chronic condition healthcare delivery.

Cambodian and Laotian students (CLS) are among the largest groups of international students in intra-ASEAN student mobility as well as in Vietnamese higher education institutions (HEIs). However, little has been researched on the factors influencing CLS’s decision to choose Vietnam as destination country. The purpose of this study is to investigate why CLS decide to go overseas and choose Vietnam as their host country among other opportunities as well as their perceptions of the decision.

Using qualitative methods and employing purposive sampling, data were collected by semi-structured interviews from CLS studying in a HEI in the Mekong Delta of Vietnam. The data were analysed against the push–pull framework to understand factors influencing the participants’ decision.

The findings show that CLS in the study were “pushed” by the perceived higher value of a foreign qualification and family encouragements. In terms of pull factors, they were attracted to choose Vietnam as the host country most observably due to scholarship opportunities. However other pull factors were also significant, especially the lack of certain skills in home countries and its congruence with Vietnam’s competitive strength in offering courses for those skills. In retrospect, the participants expressed a sense of optimism, though there was also certain reservation.

The small sample restrict the generalisability of the findings.

As an exploratory study, the findings can lay the ground for largerscale studies investigating CLS mobility in Vietnam and be employed for inbound student mobility policymaking reference for HEIs in Vietnam as well as in other developing countries.

This study investigates why Cambodian and Laotian international students decide to go to Vietnam, a developing country in the lesser-known part of international student mobility landscape. This is a topic that remains under-researched in the Asia-bound student mobility literature. Insights from the study can not only contribute to the scholarly gap but also offer implications for HEIs in Vietnam and other Asian countries.

The paper aims to explore the roles and impact of design in incubating and accelerating social enterprises. It aims to understand design’s influence on social enterprise ecosystems and in improving outcomes for social enterprises.

The study used an exploratory, qualitative approach, using case studies and interviews. The comparative case-study methodology was applied to evaluate the influence of design on the development of social enterprises in the UK and South Korea and identify critical issues in their utilisation of design. Empirical data included: in-depth case studies of design utilisation practices (UK = 6; South Korea = 15) and design applications (UK = 2; South Korea = 2) for the growth of social enterprise and its ecosystem; 27 social enterprise/design experts (UK = 17; South Korea = 10); and 22 social enterprises (UK = 12; South Korea = 10). Content and thematic analysis were used to synthesise the findings.

Findings demonstrate the differing influences of design on social enterprise, from improving products/services and business models to enhancing social enterprise ecosystem support and networks. Future directions are suggested for applying design for social enterprise growth, business stage development and systematising interactions between the social enterprise and design sectors.

The research is based on case studies from only two countries. Further, the adoption of working definitions of social enterprise in the countries may result in the research underestimating the heterogeneity of social enterprise.

The findings contribute to optimising efficient ecosystem development to improve social enterprise competitiveness and innovation.

This paper establishes a research foundation on design for social enterprise, offering theoretical and practical insights into its impact on growth.

This study aims to evaluate the quality of the energy efficiency disclosures made by Australian cities. As cities are significant energy users, and energy use is a crucial source of greenhouse gas emissions, energy efficiency initiatives can play an essential role in addressing climate change. Yet, little is understood about the energy efficiency disclosures being made.

The authors developed an original energy efficiency disclosure index to assess the reporting quality of the eight largest Australian cities. The websites of these cities were analysed for information on energy efficiency measures from December 2018 to June 2019. Annual reports, environmental reports, climate action plans and any other material related to energy plans were downloaded and then coded using the index.

While all cities provided energy efficiency information, little financial information was provided, limited forward-looking information was disclosed, key challenges were not disclosed, and each city provided energy efficiency disclosures differently. Collectively, these findings demonstrate that public accountability is limited.

An important implication is the need to standardise and improve cities’ energy efficiency reporting, especially concerning financial information. Cities, governments and the Carbon Disclosure Project (formerly the CDP) could achieve this, perhaps as part of the broader update of the CDP city-focused guidelines for greenhouse gas (GHG) reporting.

Although some studies on GHG reporting by cities have already been undertaken, including energy efficiency as part of their disclosure index, no study has focused on energy efficiency disclosures. The authors provide original insights concerning these practices. The study also provides an energy efficiency disclosure index that can be used in further research.

The purpose of this study is to propose and explore a conceptualization of decisional capital that is suitable for early career teachers.

This study uses exploratory factor analysis on a sample of early career teachers to examine a literature-derived conceptualization of decisional capital.

The factors that emerged support the literature-derived conceptualization. A subsequent confirmatory factor analysis on a second sample of early career teachers offers additional evidence for the proposed conceptualization. An exploration of the underlying factor structure comparing results across four competing models (i.e. unidimensional, correlated factors, second order, and bifactor) suggests that a second order factor explains the variance across the three proposed factors well. We conclude that this second order factor is decisional capital.

This is the first study that examines the discrete elements of decisional capital. Understanding these discrete elements is an avenue for investigation into the development of decisional capital beyond the acknowledgment that it takes time to develop.