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Book part
Publication date: 24 August 2011

Morten H. Abrahamsen

The study here examines how business actors adapt to changes in networks by analyzing their perceptions or their network pictures. The study is exploratory or iterative in…

Abstract

The study here examines how business actors adapt to changes in networks by analyzing their perceptions or their network pictures. The study is exploratory or iterative in the sense that revisions occur to the research question, method, theory, and context as an integral part of the research process.

Changes within networks receive less research attention, although considerable research exists on explaining business network structures in different research traditions. This study analyzes changes in networks in terms of the industrial network approach. This approach sees networks as connected relationships between actors, where interdependent companies interact based on their sensemaking of their relevant network environment. The study develops a concept of network change as well as an operationalization for comparing perceptions of change, where the study introduces a template model of dottograms to systematically analyze differences in perceptions. The study then applies the model to analyze findings from a case study of Norwegian/Japanese seafood distribution, and the chapter provides a rich description of a complex system facing considerable pressure to change. In-depth personal interviews and cognitive mapping techniques are the main research tools applied, in addition to tracer studies and personal observation.

The dottogram method represents a valuable contribution to case study research as it enables systematic within-case and across-case analyses. A further theoretical contribution of the study is the suggestion that network change is about actors seeking to change their network position to gain access to resources. Thereby, the study also implies a close relationship between the concepts network position and the network change that has not been discussed within the network approach in great detail.

Another major contribution of the study is the analysis of the role that network pictures play in actors' efforts to change their network position. The study develops seven propositions in an attempt to describe the role of network pictures in network change. So far, the relevant literature discusses network pictures mainly as a theoretical concept. Finally, the chapter concludes with important implications for management practice.

Details

Interfirm Networks: Theory, Strategy, and Behavior
Type: Book
ISBN: 978-1-78052-024-7

Keywords

Book part
Publication date: 30 May 2013

Peter J. Buckley, Timothy M. Devinney and Ryan W. Tang

Over the past decade, international business and international management researchers have utilized meta-analytic approaches to synthesizing findings in the extant…

Abstract

Over the past decade, international business and international management researchers have utilized meta-analytic approaches to synthesizing findings in the extant literature. This chapter reviews the studies published in the top five international business and management journals from 2004 to 2012. The review investigates major problems in the published meta-analyses by evaluating their overall analyses as well as the approaches utilized. The findings of this review reveal differences among the journals and improvements in the approaches applied in recent years. The chapter ends by discussing why and how international business and management researchers need to focus more on methodological fundamentals in their applications of meta-analysis.

Details

Philosophy of Science and Meta-Knowledge in International Business and Management
Type: Book
ISBN: 978-1-78190-713-9

Book part
Publication date: 28 September 2015

Md Shah Azam

Information and communications technology (ICT) offers enormous opportunities for individuals, businesses and society. The application of ICT is equally important to…

Abstract

Information and communications technology (ICT) offers enormous opportunities for individuals, businesses and society. The application of ICT is equally important to economic and non-economic activities. Researchers have increasingly focused on the adoption and use of ICT by small and medium enterprises (SMEs) as the economic development of a country is largely dependent on them. Following the success of ICT utilisation in SMEs in developed countries, many developing countries are looking to utilise the potential of the technology to develop SMEs. Past studies have shown that the contribution of ICT to the performance of SMEs is not clear and certain. Thus, it is crucial to determine the effectiveness of ICT in generating firm performance since this has implications for SMEs’ expenditure on the technology. This research examines the diffusion of ICT among SMEs with respect to the typical stages from innovation adoption to post-adoption, by analysing the actual usage of ICT and value creation. The mediating effects of integration and utilisation on SME performance are also studied. Grounded in the innovation diffusion literature, institutional theory and resource-based theory, this study has developed a comprehensive integrated research model focused on the research objectives. Following a positivist research paradigm, this study employs a mixed-method research approach. A preliminary conceptual framework is developed through an extensive literature review and is refined by results from an in-depth field study. During the field study, a total of 11 SME owners or decision-makers were interviewed. The recorded interviews were transcribed and analysed using NVivo 10 to refine the model to develop the research hypotheses. The final research model is composed of 30 first-order and five higher-order constructs which involve both reflective and formative measures. Partial least squares-based structural equation modelling (PLS-SEM) is employed to test the theoretical model with a cross-sectional data set of 282 SMEs in Bangladesh. Survey data were collected using a structured questionnaire issued to SMEs selected by applying a stratified random sampling technique. The structural equation modelling utilises a two-step procedure of data analysis. Prior to estimating the structural model, the measurement model is examined for construct validity of the study variables (i.e. convergent and discriminant validity).

The estimates show cognitive evaluation as an important antecedent for expectation which is shaped primarily by the entrepreneurs’ beliefs (perception) and also influenced by the owners’ innovativeness and culture. Culture further influences expectation. The study finds that facilitating condition, environmental pressure and country readiness are important antecedents of expectation and ICT use. The results also reveal that integration and the degree of ICT utilisation significantly affect SMEs’ performance. Surprisingly, the findings do not reveal any significant impact of ICT usage on performance which apparently suggests the possibility of the ICT productivity paradox. However, the analysis finally proves the non-existence of the paradox by demonstrating the mediating role of ICT integration and degree of utilisation explain the influence of information technology (IT) usage on firm performance which is consistent with the resource-based theory. The results suggest that the use of ICT can enhance SMEs’ performance if the technology is integrated and properly utilised. SME owners or managers, interested stakeholders and policy makers may follow the study’s outcomes and focus on ICT integration and degree of utilisation with a view to attaining superior organisational performance.

This study urges concerned business enterprises and government to look at the environmental and cultural factors with a view to achieving ICT usage success in terms of enhanced firm performance. In particular, improving organisational practices and procedures by eliminating the traditional power distance inside organisations and implementing necessary rules and regulations are important actions for managing environmental and cultural uncertainties. The application of a Bengali user interface may help to ensure the productivity of ICT use by SMEs in Bangladesh. Establishing a favourable national technology infrastructure and legal environment may contribute positively to improving the overall situation. This study also suggests some changes and modifications in the country’s existing policies and strategies. The government and policy makers should undertake mass promotional programs to disseminate information about the various uses of computers and their contribution in developing better organisational performance. Organising specialised training programs for SME capacity building may succeed in attaining the motivation for SMEs to use ICT. Ensuring easy access to the technology by providing loans, grants and subsidies is important. Various stakeholders, partners and related organisations should come forward to support government policies and priorities in order to ensure the productive use of ICT among SMEs which finally will help to foster Bangladesh’s economic development.

Details

E-Services Adoption: Processes by Firms in Developing Nations
Type: Book
ISBN: 978-1-78560-325-9

Keywords

Article
Publication date: 17 November 2022

Sungwon Oh, Min Jae Park, Tae You Kim and Jiho Shin

This study aimed to present the methodology of the text data analysis to establish marketing strategies for fintech companies in a practical way. Specifically, the…

Abstract

Purpose

This study aimed to present the methodology of the text data analysis to establish marketing strategies for fintech companies in a practical way. Specifically, the methodology was presented to convert customers' review data, which consisted of the text data (unstructured data), to the numerical data (structured data) by using a text mining algorithm “Global Vectors for Word Representation,” abbreviated as “GloVe”; additionally, the authors presented the methodology to deploy the numerical data for marketing strategies with eliminate-reduce-raise-create (ERRC) value factor analytics.

Design/methodology/approach

First, the authors defined the background, features and contents of fintech services based on a review of related literature review. Additionally, they examined business strategies, the importance of social media for fintech services and fintech technology trends based on the literature review. Next, they analyzed the similarity between fintech-related keywords, which represent the trends in fintech services, and the text data related to fintech corporations and their services posted on Facebook and Twitter, which are two of the most popular social media globally, during the period 2017–2019. The similarity was then quantified and categorized in terms of the representative global fintech companies and the status of each fintech service sector. Furthermore, the similarity was visualized, and value elements were rebuilt using ERRC strategy analytics.

Findings

This study is meaningful in that it quantifies the degree of similarity between customers' responses, experiences and expectations regarding the rapidly growing global fintech firms' services and trends in fintech services.

Originality/value

This study suggests a practical way to apply in business by providing a method for transforming unstructured text data into structured numerical data it is measurable. It is expected that this study can be used as the basis for exploring sustainable development strategies for the fintech industry.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

Keywords

Article
Publication date: 17 May 2022

Qiucheng Liu

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the…

Abstract

Purpose

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Design/methodology/approach

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Findings

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Originality/value

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

Article
Publication date: 5 April 2022

Stefan Strohmeier, Julian Collet and Rüdiger Kabst

Enabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve…

Abstract

Purpose

Enabled by increased (“big”) data stocks and advanced (“machine learning”) analyses, the concept of human resource analytics (HRA) is expected to systematically improve decisions in human resource management (HRM). Since so far empirical evidence on this is, however, lacking, the authors' study examines which combinations of data and analyses are employed and which combinations deliver on the promise of improved decision quality.

Design/methodology/approach

Theoretically, the paper employs a neo-configurational approach for founding and conceptualizing HRA. Methodically, based on a sample of German organizations, two varieties (crisp set and multi-value) of qualitative comparative analysis (QCA) are employed to identify combinations of data and analyses sufficient and necessary for HRA success.

Findings

The authors' study identifies existing configurations of data and analyses in HRM and uncovers which of these configurations cause improved decision quality. By evidencing that and which combinations of data and analyses conjuncturally cause decision quality, the authors' study provides a first confirmation of HRA success.

Research limitations/implications

Major limitations refer to the cross-sectional and national sample and the usage of subjective measures. Major implications are the suitability of neo-configurational approaches for future research on HRA, while deeper conceptualizing and researching both the characteristics and outcomes of HRA constitutes a core future task.

Originality/value

The authors' paper employs an innovative theoretical-methodical approach to explain and analyze conditions that conjuncturally cause decision quality therewith offering much needed empirical evidence on HRA success.

Details

Baltic Journal of Management, vol. 17 no. 3
Type: Research Article
ISSN: 1746-5265

Keywords

Book part
Publication date: 19 October 2020

Anat Rafaeli, Galit Bracha Yom Tov, Shelly Ashtar and Daniel Altman

Purpose: To outline recent developments in digital service delivery in order to encourage researchers to pursue collaborations with computer science, operations research…

Abstract

Purpose: To outline recent developments in digital service delivery in order to encourage researchers to pursue collaborations with computer science, operations research, and data science colleagues and to show how such collaborations can expand the scope of research on emotion in service delivery.

Design/methodology/approach: Uses archived resources available at http://LivePerson.com to extract data based in genuine service conversations between agents and customers. We refer to these as “digital traces” and analyze them using computational science models.

Findings: Although we do not test significance or causality, the data presented in this chapter provide a unique lens into the dynamics of emotions in service; results that are not obtainable using traditional research methods.

Research limitations/implications: This is a descriptive study where findings unravel new dynamics that should be followed up with more research, both research using traditional experimental methods, and digital traces research that allows inferences of causality.

Practical implications: The digital data and newly developed tools for sentiment analyses allow exploration of emotions in large samples of genuine customer service interactions. The research provides objective, unobtrusive views of customer emotions that draw directly from customer expressions, with no self-report intervention and biases.

Originality/value: This is the first objective and detailed depiction of the actual emotional encounters that customers express, and the first to analyze in detail the nature and content of customer service work.

Book part
Publication date: 30 September 2020

Zophia Edwards

In recent decades, it has become clear that the major economic, political, and social problems in the world require contemporary development research to examine…

Abstract

In recent decades, it has become clear that the major economic, political, and social problems in the world require contemporary development research to examine intersections of race and class in the global economy. Theorists in the Black Radical Tradition (BRT) were the first to develop and advance a powerful research agenda that integrated race–class analyses of capitalist development. However, over time, progressive waves of research streams in development studies have successively stripped these concepts from their analyses. Post-1950s, class analyses of development overlapped with some important features of the BRT, but removed race. Post-1990s, ethnicity-based analyses of development excised both race and class. In this chapter, I discuss what we learn about capitalist development using the integrated race–class analyses of the BRT, and how jettisoning these concepts weakens our understanding of the political economy of development. To remedy our current knowledge gaps, I call for applying insights of the BRT to our analyses of the development trajectories of nations.

Details

Rethinking Class and Social Difference
Type: Book
ISBN: 978-1-83982-020-5

Keywords

Book part
Publication date: 18 July 2006

Andreas Rauch and Michael Frese

We argue that entrepreneurship research should use meta-analysis to integrate the findings of the field. A meta-analytical approach has several advantages as compared with…

Abstract

We argue that entrepreneurship research should use meta-analysis to integrate the findings of the field. A meta-analytical approach has several advantages as compared with narrative reviews: First, narrative reviews are likely to bias empirical evidence because they are limited by the information-processing capacities of the reviewers (Tett, Jackson, & Rothstein, 1991). This is often a downward bias leading to the conclusion of little positive knowledge in the field. For example, frequency counts of significant results ignore sampling errors of individual studies, reliability problems of instruments, range restrictions of samples, dichotomization of continuous variables, imperfect construct validity, and extraneous factors (Hunter & Schmidt, 2004). These issues usually result in a higher incidence of Type II errors (i.e., rejecting the hypothesis wrongly). Thus, narrative reviews are more likely to lead to the conclusion that there are no relationships between independent and dependent variables in entrepreneurship when in fact they are (Hunter & Schmidt, 1990; Tett et al., 1991). Second, meta-analysis accumulates studies based on a set of explicit decision rules and, therefore, is less biased by subjective perceptions of the reviewer than narrative reviews. Meta-analyses require judgments as well, e.g., when defining the area of the study or coding moderator variables. However, the decisions are public and open to criticism and replication by other scientists (Johnson & Eagly, 2000). Third, meta-analysis is based on many studies and, thus, avoids the influence of single studies. Fourth, meta-analysis controls for sampling error variance and, thus, controls for power deficits of individual studies (Hunter & Schmidt, 2004). For example, the Brockhaus and Nord (1979) study is frequently cited in the entrepreneurship literature for providing evidence that there is no relationship of personality characteristics with entrepreneurship. However, this study is based on a small sample of 31 business owners and therefore, has serious statistical power problems. Noteworthy, the effect sizes of small samples are less precise in estimating a population value than effect sizes of larger samples. Fifth, meta-analyses can correct many errors of individual studies (Hunter & Schmidt, 2004). Since meta-analyses estimate population correlations between given variables, it is important to correct for errors of studies (e.g., unreliability, range restriction, and sampling error) to achieve unbiased estimates. Sixth, meta-analysis allows an assessment of the magnitude of relationships and, thus, provides more precise and often comparable assessments of the validity of concepts. Thus, meta-analyses support the assessment of the practical significance of findings. Seventh, meta-analysis tests for variations in relationships across studies and, therefore, allows an assessment of the generalizeability of effects. If the size of reported relationships varies considerably between different studies, there will be context conditions that account for these variations. These context conditions are moderators that affect the size of relationships. The moderators may include study characteristics, method moderators, and theoretical moderators. Thus, meta-analyses also help to identify areas for new studies. Finally, meta-analysis techniques allow to test more than one independent and/or moderator variable by using methods based on regression analysis (Lipsey & Wilson, 2001). Using such procedures allows to estimate the independent contribution of variables on results, to control for methodological variables, and to test the interactions between moderator variables.

Details

Entrepreneurship: Frameworks And Empirical Investigations From Forthcoming Leaders Of European Research
Type: Book
ISBN: 978-1-84950-428-7

Book part
Publication date: 8 October 2020

Jeremy D. Mackey, Charn P. McAllister, Liam P. Maher and Gang Wang

Recently, there has been an increase in the number and type of studies in the organizational sciences that examine curvilinear relationships. These studies are important…

Abstract

Recently, there has been an increase in the number and type of studies in the organizational sciences that examine curvilinear relationships. These studies are important because some relationships have context-specific inflection points that alter their magnitude and/or direction. Although some scholars have utilized basic techniques to make meta-analytic inferences about curvilinear effects with the limited information available about them, there is still a tremendous opportunity to advance our knowledge by utilizing rigorous techniques to meta-analytically examine curvilinear effects. In a recent study, we used a novel meta-analytic approach in an effort to comprehensively examine curvilinear relationships between destructive leadership and followers' workplace outcomes. The purpose of this chapter is to provide an actionable guide for conducting curvilinear meta-analyses by describing the meta-analytic techniques we used in our recent study. Our contributions include a detailed guide for conducting curvilinear meta-analyses, the useful context we provide to facilitate its implementation, and our identification of opportunities for scholars to leverage our technique in future studies to generate nuanced knowledge that can advance their fields.

Details

Advancing Methodological Thought and Practice
Type: Book
ISBN: 978-1-80043-079-2

Keywords

1 – 10 of over 240000