Barriers to radical innovation in research institutions in China

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jianhua Yang ◽  
Rafif Al-Sayed
Keyword(s):  
Theoretical Model ◽  
Latent Variables ◽  
Structural Equation ◽  
Business Models ◽  
Research Collaboration ◽  
Statistical Significance ◽  
Radical Innovation ◽  
Equation Modeling ◽  
Research Institutions ◽  
Content Type

Purpose This study aims to develop a better understanding of radical innovation performance and proposes a comprehensive and theoretical model of the barriers impeding radical innovation from the perspective of researchers working in research institutions in China. Both quantitative and qualitative techniques were used to test the hypotheses regarding barriers to radical innovation and the model proposed in this research. Design/methodology/approach The data was collected through questionnaires and semi-structured interviews with researchers from different research institutions across several cities in China. Next, the data was analyzed by deploying the structural equation modeling technique and calculating the statistical significance of correlations, regression and path coefficients among the latent variables. Findings The results indicated the major barriers impeding radical innovation in Chinese research institutes. Based on these findings, suggested policies, regulations and business models are put forward that can promote radical innovation in these institutes through increasing research freedom, enhancing organizational flexibility, attracting talented researchers and expanding research collaboration. Originality/value The research proposes a comprehensive and theoretical model of the barriers impeding radical innovation from the perspective of researchers working in research institutions in China.

Privacy helplessness on social media: its constituents, antecedents and consequences

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hichang Cho
Keyword(s):  
Theoretical Model ◽  
Structural Equation ◽  
Factor Model ◽  
Measurement Model ◽  
Equation Modeling ◽  
Confirmatory Factor Analyses ◽  
Content Type ◽  
Internet Users ◽  
The Usa ◽  
Antecedents And Consequences

PurposeMany internet users exhibit signs of privacy helplessness and entirely give up online privacy management. However, we know little about what privacy helplessness is, when users are likely to experience it and its implications for privacy behavior. The objectives of this study were twofold: (a) the conceptual explication of privacy helplessness as a novel construct in privacy research and (b) the development of a theoretical model that specifies the antecedents and consequences of privacy helplessness.Design/methodology/approachA research model of privacy helplessness that contains three subcomponents of privacy helplessness, five antecedents and one outcome was developed. The model was empirically examined based on survey data collected from 589 Facebook users in the USA.FindingsThe results of exploratory and confirmatory factor analyses showed that privacy helplessness is adequately assessed by a three-factor model with affective, cognitive and motivational components. The results of structural equation modeling indicated that these three aspects of privacy helplessness are uniquely predicted by five theoretical factors: (a) prior experience of privacy risks, (b) personal mastery, (c) perceived costs of adaptive privacy actions, (d) perceived rewards of privacy inactions and (e) perceived vulnerability. Furthermore, it was found that helplessness as motivational deficits (and cognitive helplessness via this) impedes adaptive privacy actions, while cognitive helplessness promotes adaptive privacy actions when they do not result in motivational deficits.Originality/valueThis study pioneers investigation in understanding key constituents, attributes and processes underlying privacy helplessness. First, the present study developed the first theory-derived, successively validated measurement model of privacy helplessness. Second, this research proposed a theoretical model of privacy helplessness, specifying antecedents and consequences of privacy helplessness.

From managing customers to joint venturing with customers: co-creating service value in the digital age

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Christine Falkenreck ◽  
Ralf Wagner
Keyword(s):  
Perceived Risk ◽  
Structural Equation ◽  
Business Models ◽  
Joint Venture ◽  
Digital Age ◽  
Partial Least Square ◽  
Least Square ◽  
Equation Modeling ◽  
Data Set ◽  
Content Type

Purpose Until today, scholars claim that the phenomenon of “co-creation” of value in an “interacted” economy and in the context of positive actor-to-actor relationships has not been adequately explored. This study aims to first to identify and separate the accessible values of internet of things (IoT)-based business models for business-to-business (B2B) and business-to-government (B2G) customer groups. It quantifies the drivers to successfully implement disruptive business models. Design/methodology/approach Data were gathered from 292 customers in Western Europe. The conceptual framework was tested using partial least square structural equation modeling. Findings Managing disruptions in the digital age is closely related to the fact that the existing trust in buyer-seller relationships is not enough to accept IoT projects. A company’s digitalization capabilities, satisfaction with the existing relationship and trust in the IoT credibility of the manufacturer drives the perceived value of IoT-based business models in B2B settings. Contrastingly, in B2G settings, money is less important. Research limitations/implications Research refers to one business field, the data set is of European origin only. Findings indicate that the drivers to engage in IoT-related projects differ significantly between the customer groups and therefore require different marketing management strategies. Saving time today is more important to B2G buyers than saving money. Practical implications The disparate nature of B2B and B2G buyers indicates that market segmentation and targeted marketing must be considered before joint-venturing in IoT business models. To joint venture supply chain partners co-creating value in the context of IoT-related business models, relationship management should be focused with buyers on the same footing, as active players and co-developers of a personalized experience in digital service projects. Originality/value Diverging from established studies focusing on the relationship within a network of actors, this study defines disruptive business models and identifies its drivers in B2B and B2G relationships. This study proposes joint venturing with B2B and B2G customers to overcome the perceived risk of these IoT-related business models. Including customers in platforms and networks may lead to the co-creation of value in joint IoT projects.

scholarly journals Impact of big data and predictive analytics capability on supply chain sustainability

2018 ◽  
Vol 29 (2) ◽  
pp. 513-538 ◽  
Author(s):  
Shirish Jeble ◽  
Rameshwar Dubey ◽  
Stephen J. Childe ◽  
Thanos Papadopoulos ◽  
David Roubaud ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Theoretical Model ◽  
Performance Measures ◽  
Structural Equation ◽  
Predictive Analytics ◽  
Equation Modeling ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
The Impact

PurposeThe purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.Design/methodology/approachThe authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.FindingsThe statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support forH4. Although the authors did not find support forH4(moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.Originality/valueThis study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.

A structural equation model for big data adoption in the healthcare supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dindayal Agrawal ◽  
Jitender Madaan
Keyword(s):  
Factor Analysis ◽  
Big Data ◽  
Supply Chain ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Model ◽  
Equation Modeling ◽  
Data Governance ◽  
Social Perspective ◽  
Content Type

PurposeThe purpose of this study is to examine the barriers to the implementation of big data (BD) in the healthcare supply chain (HSC).Design/methodology/approachFirst, the barriers concerning BD adoption in the HSC were found by conducting a detailed literature survey and with the expert's opinion. Then the exploratory factor analysis (EFA) was employed to categorize the barriers. The obtained results are verified using the confirmatory factor analysis (CFA). Structural equation modeling (SEM) analysis gives the path diagram representing the interrelationship between latent variables and observed variables.FindingsThe segregation of 13 barriers into three categories, namely “data governance perspective,” “technological and expertise perspective,” and “organizational and social perspective,” is performed using EFA. Three hypotheses are tested, and all are accepted. It can be concluded that the “data governance perspective” is positively related to “technological and expertise perspective” and “organizational and social perspective” factors. Also, the “technological and expertise perspective” is positively related to “organizational and social perspective.”Research limitations/implicationsIn literature, very few studies have been performed on finding the barriers to BD adoption in the HSC. The systematic methodology and statistical verification applied in this study empowers the healthcare organizations and policymakers in further decision-making.Originality/valueThis paper is first of its kind to adopt an approach to classify barriers to BD implementation in the HSC into three distinct perspectives.

Trust factors for organic foods: consumer buying behavior

2019 ◽  
Vol 122 (2) ◽  
pp. 414-431 ◽  
Author(s):  
Tsung Hung Lee ◽  
Chung-Jen Fu ◽  
Yin Yuan Chen
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Organic Food ◽  
Equation Modeling ◽  
Small Scale ◽  
Buying Behavior ◽  
Organic Foods ◽  
Behavior Theory ◽  
Content Type ◽  
Trust Factors

Purpose The purpose of this paper is to assess the relationship between trust factors and buying behavior among consumers in the organic food market in Taiwan. Design/methodology/approach The researchers developed a questionnaire using latent variables including the trust factors, utilitarian attitudes, hedonic attitudes, buying behavior and demographic information of consumers of organic foods. Confirmatory factor analysis and the structural equation modeling were conducted using LISREL 8.80 for Windows. Findings The empirical results indicated that health content, locally produced products, organic food labels and price premiums positively and significantly affected utilitarian and hedonic attitudes. Both utilitarian attitudes and hedonic attitudes positively and significantly affected respondents’ buying behavior. A series of theoretical implications were identified. Practical implications The researchers concluded that providing consumers with practical information related to organic food, establishing local production facilities, developing content, standardizing labeling procedures and promoting a new organic certification system for small-scale producers will encourage more consumers to purchase organic food. Originality/value This study first examines the food trust buying behavior of organic foods and related consumption behavior theory questions. It mainly takes the stimulus–organism–response model as the foundation of its approach. Simultaneously, it also conforms to utilitarian behavior theory, and the process by which consumers become better aware of organic foods’ quality.

Rethinking balanced scorecard (BSC) measures: formative versus reflective measurement models

2017 ◽  
Vol 66 (1) ◽  
pp. 92-110 ◽  
Author(s):  
Sungbum Park ◽  
Heeseok Lee ◽  
Seong Wook Chae
Keyword(s):  
Balanced Scorecard ◽  
Latent Variables ◽  
Structural Equation ◽  
Model Comparison ◽  
Empirical Studies ◽  
Equation Modeling ◽  
Content Type ◽  
Formative Measurement ◽  
Measurement Models ◽  
Formative Indicators

Purpose Most empirical balanced scorecard (BSC) studies have shown a tendency to wrongly employ reflective indicators instead of the more theoretically suitable formative indicators. However, formative indicators are difficult to apply due to the lack of statistical software support and a standardized model testing method. The paper aims to discuss these issues. Design/methodology/approach This study empirically compares the reflective and formative measurement method with standardized model comparison criteria. After collecting 217 valid questionnaires from companies in South Korea, the authors applied a structural equation modeling technique to analyze the data. Findings The result shows that the formative measure provides greater validity for the corporate performance measurement using BSC. Further, this study shows the indicators’ relative influence on each BSC perspectives using the formative measure. Practical implications This study proved the usefulness of the formative measure analysis method and suggested its practical use, focusing on the indicators most useful in developing corporate strategies. In addition, the authors showed that formative indicators could be used in the corporate environment by overcoming the limitations of conventional studies that were confined to causal relationships with latent variables. Originality/value This study may be the pioneering work that compares formative and reflective indicators simultaneously, addressing the usefulness of formative measurement and its application validity in the existing empirical studies using reflective measurements.

Extending cumulative capability models: the role of innovation in the accumulation of competitive performance

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mantas Vilkas ◽  
Inga Stankevice ◽  
Rimantas Rauleckas
Keyword(s):  
Structural Equation ◽  
Statistical Significance ◽  
Theoretical Explanation ◽  
Innovation Performance ◽  
Equation Modeling ◽  
Manufacturing Companies ◽  
Competitive Performance ◽  
Cost Performance ◽  
Content Type ◽  
Performance Dimensions

PurposeCumulative capability models are dominating frameworks explaining how manufacturing organizations gain their performance capabilities, such as quality, delivery, flexibility and cost. When innovation capabilities are excluded from the framework, the models are incapable of explaining how companies sustain substantive capabilities in a changing environment. Responding to this gap, the purpose of this paper is to propose and test a “sand cone” cumulative capability model that includes the innovation competitive performance alongside the competitive performance of quality, delivery flexibility and cost.Design/methodology/approachTwo competing cumulative models were proposed. The extended cumulative capability model hypothesizes the development of innovation in sequence with other competitive performance dimensions. The affected with innovation cumulative model hypothesizes innovation performance as a predecessor of other performance dimensions. The models were tested using a multimethod approach on a representative sample of 500 manufacturing companies. An analysis of correlations among competitive performance, frequencies of plants following prescribed sequences, fit statistics of covariance-based structural equation modeling and analysis of strength and statistical significance of path coefficients enabled us to select a model that best represents the collected data.FindingsThe findings reveal that innovation competitive performance operates as a predecessor of quality, delivery, flexibility and cost and is developed in relation to these performance dimensions. The modified model also provides a theoretical explanation of how innovation performance helps to sustain reliable production systems that can perform consistently over time within a tolerable range of quality, delivery, flexibility and cost performance.Practical implicationsThe results are significant for practitioners, especially for companies that are operating in volatile environments because the results provide insight on how to develop innovation competitive performance in relation to quality, delivery, flexibility and cost performance.Originality/valueThis study extends the cumulative capability models with innovation competitive performance. It advances the contingency approach on cumulative capability models.

Adoption of mobile banking services

2019 ◽  
Vol 37 (5) ◽  
pp. 1165-1189 ◽  
Author(s):  
Apostolos Giovanis ◽  
Pinelopi Athanasopoulou ◽  
Costas Assimakopoulos ◽  
Christos Sarmaniotis
Keyword(s):  
Theory Of Planned Behavior ◽  
Technology Acceptance ◽  
Planned Behavior ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Statistical Significance ◽  
Explanatory Power ◽  
Equation Modeling ◽  
Mobile Banking ◽  
Content Type

PurposeThe purpose of this paper is to investigate which of four well-established theoretical models (i.e. technology acceptance model, theory of planned behavior, unified theory of acceptance and use of technology, decomposed theory of planned behavior (DTPB)) best explains potential users’ behavioral intentions to adopt mobile banking (MB) services.Design/methodology/approachDrawing on data from 931 potential users in Greece, the structural equation modeling method was used to examine and compare the four models in goodness-of-fit, explanatory power and statistical significance of path coefficients.FindingsResults indicate that the best model is an extension of the DTPB with perceived risk (PR). Customers’ attitude, determined by three rationally-evaluated MB attributes (usefulness, easiness and compatibility), is the main driver of consumers’ intentions to adopt MB services. Additionally, consumers’ perceptions of availability of knowledge, resources and opportunities necessary for using the service, and the pressure of interpersonal and external social contexts toward the use of MB are the other two, less important, adoption drivers. Finally, PR negatively affects attitude formation and inhibits willingness to use MB services.Practical implicationsFindings can help marketers of financial institutions to select the more parsimonious model to develop appropriate marketing strategies to increase adoption rates of MB services.Originality/valueThis is the first study that compares the performance of four well-known innovation adoption models to explain consumers’ behavior in the MB context.

The moderating role of 360-degree appraisal between engagement and innovative behaviors

2019 ◽  
Vol 69 (2) ◽  
pp. 361-381 ◽  
Author(s):  
Silva Karkoulian ◽  
Jordan Srour ◽  
Leila Canaan Messarra
Keyword(s):  
Resource Use ◽  
Latent Variables ◽  
Structural Equation ◽  
Idea Generation ◽  
Financial Resource ◽  
Work Behavior ◽  
Equation Modeling ◽  
Content Type ◽  
The Relationship ◽  
Innovative Behaviors

Purpose Engaged employees are a critical asset in any business. This is largely because engaged employees tend to proffer innovative solutions to complex problems in the workplace. The purpose of this paper is to examine the relationship between engagement and innovation as moderated by the use of 360-degree evaluation. Design/methodology/approach A survey targeting employees in Lebanon solicited their perceptions of 360-degree evaluation, engagement and innovative behaviors along with a statement as to whether their firm used 360-degree evaluations or not. Structural equation modeling (SEM) was used to test the moderating effect of 360-degree evaluations on the latent variables of engagement and three facets of innovation. Findings SEM results show that 360-degree evaluations serve to enhance engaged employees’ innovative work behavior. However, ideation (creation and implementation) behaviors are more strongly influenced by the presence of 360-degree evaluation as compared to their “tangible” counterpart (technology and financial resource use). Research limitations/implications Respondents selected for this research were randomly sampled employees in Lebanon. A stronger study strategy would be to study paired departments within organizations – one implementing 360-degree evaluation and another not implementing it. Practical implications Managers, seeking to engender and strengthen innovative behaviors in engaged employees, should utilize 360-degree evaluation processes. Furthermore, the 360-degree evaluations should be designed to probe both tangible (technology and financial resource use) and intangible (idea generation and implementation) facets of innovation. Originality/value This study yields a deeper understanding of the relationship between engagement and innovative behaviors in the workplace along with managerial insights into the design and use of 360-degree evaluation.

Online Advertising

2017 ◽  
Vol 8 (4) ◽  
pp. 1-17
Author(s):  
Mehdi Behboudi ◽  
Amir Abedini Koshksaray
Keyword(s):  
Gender Differences ◽  
Theoretical Model ◽  
Latent Variables ◽  
Structural Equation ◽  
Online Advertising ◽  
Equation Modeling ◽  
The Internet ◽  
Negative Experience ◽  
Key Dimensions ◽  
S Model

This study expands previous models of avoidance on online advertising, in particular, Cho and Cheon (2004)'s model, and examines two new dimensions on why people avoid advertising on the Internet. The study presents a comprehensive theoretical model and examines seven exogenous latent variables based on structural equation modeling, SEM. By using SEM the authors found that seven latent variables including user-perceived ad quality, internet life style, primary motives, gender differences (initial ad avoidance), perceived ad clutter, prior negative experience, and perceived goal impediment (further ad avoidance) collectively explain why people avoid advertising on the Internet. The authors found that avoidance has two key dimensions «initial ad avoidance» and «further ad avoidance.”

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