Search results

This study aims to investigate how brand name (home-emerging-country vs foreign-developed-country brand name) applied by emerging market company in conjunction with revealing the actual country-of-brand-origin (COBO) (revealed vs non-revealed origin from developed vs emerging country) affects purchase intensions of durable goods.

An experimental conjoint analysis and multilevel linear models were applied.

Results demonstrate that brand name differentiates consumers’ purchase intentions. However, not every foreign-developed-country brand name may lead to the increase of purchase intentions. Revealing the actual emerging market’s COBO for brands with developed-country brand name may lead to lowering purchase intentions. Moreover, consumer ethnocentrism and materialism moderate the relationship between the brand type in terms of brand name and purchase intentions.

This study contributes to the international marketing literature by simultaneous examination of the impact of brand name type and revealing actual COBO on purchase intentions and the moderating effects of ethnocentrism and materialism, in emerging markets’ context. It also offers novel insights for brand managers regarding the influence of emerging markets’ companies branding strategies on consumer purchase intentions.

The use of structured literature review methods like bibliometric analysis is growing in the management fields, but there is limited knowledge on how they can be facilitated by technology. Hence, we conducted a broad overview of software tools, their roles, and limitations in structured (bibliometric) literature reviewing activities. Subsequently, we show that several software tools are freely available to aid in searching the literature, identifying/ extracting relevant publications, screening/assessing quality of the extracted data, and performing analyses to generate insights from the literature. However, their applications may be confronted with several challenges such as limited analytical and functional capabilities, inadequate technological skills of researchers, and the fact that the researcher's insights are still needed to generate compelling conclusions from the results produced by software tools. Consequently, we contribute toward advancing the methodologies for performing structured reviews by providing a comprehensive and updated overview of the knowledge base of key technological software tools and the conduct of structured or bibliometric literature reviews.

Examines consumers’ perception of brands as influenced by their origins and the differences in classification ability between consumers’ knowledge levels. Specifically, culture‐of‐brand‐origin (COBO) is proposed to have replaced country‐of‐origin (COO) as the most important origin influence regarded by consumers in their perceptions of brands. Culture‐of‐brand‐origin is used to mean the cultural origin or heritage of a brand. Data were gathered from 459 respondents in the Asian city of Singapore; and used to assess Singaporean consumers’ ability to classify the cultural origins of fashion clothing brands. This was compared to their ability to classify the country origins of the same brands. Six brands were used in a between‐subjects design, with three brands of western countries and three of eastern countries. Results indicate that consumers can more readily identify the cultural origin of brands over their country‐of‐origin. Reveals that a consumer’s ability to make this distinction is influenced by the consumer’s perception of how well he/she knows the brand.

The purpose of this paper is to identify the relationships between process modeling and Industry 4.0, the strategic themes and the most used process modeling language in smart factories. The study also presents the growth of the field of study worldwide, the perspectives, main challenges, trends and suggestions for future works.

To do this, a science mapping was performed using the software SciMAT, supported by VOS viewer.

The results show that the Business Process Model and Notation (BPMN), Unified Modelling Language (UML) and Petri Net are the most relevant languages to smart manufacturing. The authors also highlighted the need to develop new languages or extensions capable of representing the dynamism, interoperability and multiple technologies of smart factories.

It was possible to identify the most used process modeling languages in smart environments and understand how these languages assist control and manage smart processes. Besides, the authors highlighted challenges, new perspectives and the need for future works in the field.

This research aims to determine the contribution of publications in the context of Türkiye to the international entrepreneurship literature between 2005 and 2022. We examined 471 articles published in international journals in the Web of Science (WoS) Core Collection database using bibliometric analysis techniques. We analyzed the data with the software Biblioshiny+Bibliometrix, SciMAT, and VOSViewer. We used performance, theme and evolution, co-authorship, and document analysis in data analysis. Performance analysis findings show that the most publications were made in 2021, the journal with the most publications was sustainability, and the author with the most publications was Bakır, C. Theme and evolution analysis revealed that the motor themes were corporate entrepreneurship, gender and entrepreneurial intentions in the first period (2005–2014), while institutional entrepreneurship stood out as the niche theme. In the second period (2015–2022), “corporate entrepreneurship” and “performance” emerged as the motor themes, while the niche themes in this period were “Syrian refugees” and “entrepreneurial intentions.” Document analysis findings show that the most studied entrepreneurship types are gender, family, corporate, social, and small business, respectively. In addition, immigrant/refugee entrepreneurship is emerging as a new topic, while indigenous entrepreneurship, informal entrepreneurship, sustainable entrepreneurship, and religion entrepreneurship are the most minor studied topics in entrepreneurship. Evidence-based decision-making inputs were obtained for those holding the resource allocation authority in Türkiye. Policymakers and funders, as well as individuals and institutions that want to design the future in terms of resources, can benefit from the findings and analysis of this chapter. Türkiye, which ranks 26th in the world regarding entrepreneurship, must develop a policy based on data.

This chapter uses multiple research methods, including quantitative science mapping analysis (SciMat) and a qualitative literature review, to provide insight into the academic debate unfolding at the intersection of big data and business processes. SciMat analysis based on keyword co-occurrence enabled identifying 12 of the most productive research themes, as reflected in a poll of 301 articles about big data and business processes. The three most important themes are: firm performance, Industry 4.0, and innovation. The traditional literature review on firm performance indicated that big data analytics (BDA) positively influence business process performance and have a beneficial impact on a firm’s performance, that is, the role of big data is viewed as critical in the context of Industry 4.0 because it enhances productivity and improves business processes. The benefits of BDA can be achieved only if the organizational obstacles related to planning, workforce attitude, and alignment with strategy are overcome. Moreover, big data is perceived as a significant source of innovation in an organization and can be conceptualized with the use of a resource-based view (RBV) of the firm. BDA positively influence business processes, which is strengthened by adequate implementation and openness to innovation.

This chapter applies science mapping analysis (SciMat) and literature review as research methods to examine literature about higher education institutions (HEIs) during the Covid-19 pandemic. User acceptance, satisfaction, and perception are identified as the most productive research themes in the sample of 561 Web of Science (WoS) indexed articles about HEIs during the pandemic. The literature review of the top themes reveals that user acceptance is influenced by the perceived usefulness of online learning and ease of using online tools. The level of satisfaction among students in online learning is relatively high and linked with the perceived benefits of online courses. Conditions influencing user acceptance and perceived satisfaction differ between students and lecturers. Technology-related themes appeared to be relatively under-researched as standalone themes, but technological aspects turned out to be important components of the most prolific research themes identified.

The Cobo Hall, Detroit, Michigan, USA was the venue for the 59th Annual Meeting, Federation of Societies for Coatings Technology and the 46th Paint Industries Show which took place on October 28th‐30th, 1981. There were no fewer than 179 exhibitors, almost entirely from the USA. The large crowds on the first day indicated the popularity of the show. The only criticisms that could be made were the lack of seating accommodation for footsore visitors, and the poor quality of the cafeteria at Cobo Hall, bearing in mind that the stands (Booths in the local dialect) occupied 38,210 sq. ft. A novelty to visitors is that across the river is a different country, Canada, and Windsor, Ontario, the “frontier” town on the Canadian side, was used as a hotel base for many participants.

The authors present nine dimensions to provide structure for the many Futures of Work (FoW). This is done to advance a more sociotechnical and nuanced approach to the FoW, which is too-often articulated as singular and unidimensional. Futurists emphasize they do not predict the future, but rather, build a number of possible futures – in plural – often in the form of scenarios constructed based on key dimensions. Such scenarios help decision-makers consider alternative actions by providing structured frames for careful analyses. It is useful that the dimensions be dichotomous. Here, the authors focus specifically on the futures of knowledge work.

Building from a sustained review of the FoW literature, from a variety of disciplines, this study derives the nine dimensions.

The nine FoW dimensions are: Locus of Place, Locus of Decision-making, Structure of Work, Technologies’ Roles, Work–Life, Worker Expectations, Leadership Model, Firm’s Value Creation and Labor Market Structure. Use of the dimensions is illustrated by constructing sample scenarios.

While FoW is multi-dimensional, most FoW writing has focused on one or two dimensions, often highlighting positive or negative possibilities. Empirical papers, by their nature, are focused on just one dimension that is supported by data. However, future-oriented policy reports tend are more often multi-faceted analyses and serve here as the model for what we present.

Current literature recognised big data as a digital revolution affecting all organisational processes. To obtain a competitive advantage from the use of big data, an efficient integration in a performance measurement system (PMS) is needed, but it is still a “great challenge” in performance measurement research. This paper aims to review the big data and performance measurement studies to identify the publications’ trends and future research opportunities.

The authors reviewed 873 documents on big data and performance carrying out an extensive bibliometric analysis using two main techniques, i.e. performance analysis and science mapping.

Results point to a significant increase in the number of publications on big data and performance, highlighting a shortage of studies on business, management and accounting areas, and on how big data can improve performance measurement. Future research opportunities are identified. They regard the development of further research to explain how performance measurement field can effectively integrate big data into a PMS and describe the main themes related to big data in performance measurement literature.

This paper gives a holistic view of big data and performance measurement research through the inclusion of numerous contributions on different research streams. It also encourages further study for developing concrete tools.