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1 – 10 of 912The purpose of this paper is to integrate the findings of articles appearing in European Journal of Marketing’s special section on covariance-based versus composite-based…
Abstract
Purpose
The purpose of this paper is to integrate the findings of articles appearing in European Journal of Marketing’s special section on covariance-based versus composite-based structural equations modeling (SEM).
Design/methodology/approach
This is an editorial which uses literature review to draw conclusions regarding areas of agreement, areas for further research, and changing the discussion around composite-based SEM methods.
Findings
There are now four new areas of agreement regarding composite-based SEM. Researchers should adopt a toolbox approach to their methods and know the strengths and weaknesses of the research tools in their toolbox. Partial least squares (PLS) SEM and covariance-based SEM are not substitutes, and it is inappropriate to use the language of confirmatory factor analysis (CFA) in reporting measurement estimates from PLS SEM. Measurement matters and researchers need to devote effort to using reliable and valid multi-item measures in their investigations.
Originality/value
This postscript article outlines recommendations for authors, reviewers and editors regarding the analysis of data and reporting of results using structural equations models.
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Shweta Shweta, Dinesh Kumar and Dheeraj Chandra
One of the most important components of healthcare is the timely delivery of pharmaceutical products, such as life-saving medicines. However, disruptions like COVID-19 bring new…
Abstract
Purpose
One of the most important components of healthcare is the timely delivery of pharmaceutical products, such as life-saving medicines. However, disruptions like COVID-19 bring new challenges and risks to the pharmaceutical supply chain (PSC) and healthcare organizations that impact their operational performance. This study focuses on mitigating risks in India's generic medicine supply chain (GMSC) as a result of various disruptions, which can assist policymakers develop appropriate plans and strategies to build resilience in the Jan Aushadhi Scheme (JAS) of micro, small and medium enterprises (MSMEs) in order to improve their overall performance.
Design/methodology/approach
Risk-causing vulnerabilities and resilience capabilities are identified from the literature review and expert's opinions. Following that, the vulnerabilities are classified into cause-and-effect vulnerabilities, and supply chain resilient capabilities (SCRCs) are measured using a hybrid fuzzy DEMATEL and best worst method (FDEMATEL-BMW) framework.
Findings
The outcome of the study reveals that transportation breakdown, loss of human resources and loss of suppliers are the potential risk-causing vulnerabilities that lead to vulnerabilities like shortages of medicines, loss of in-hand stock qualities and loss of sales/revenue. In addition, the analysis suggests that the sustainability of an organization with maximum weightage is the critical factor for building resilience in GMSC followed by flexibility, agility and visibility.
Practical implications
The integration of resilience into Jan Aushadhi GMSC can help in managing disruptions efficiently and effectively to mitigate risk and optimize MSMEs overall performance.
Originality/value
To the best of the authors’ knowledge, this work will be the first of its kind to model resilience in GMSC of MSMEs using a hybrid framework.
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Vicky Dhanis Wardhana, Idris Gautama So, Dezie L. Warganegara and Mohammad Hamsal
This study aims to examine the relationship between the influence of technological disruption and the transformation of business models mediated by adaptive organization and…
Abstract
Purpose
This study aims to examine the relationship between the influence of technological disruption and the transformation of business models mediated by adaptive organization and organization learning.
Design/methodology/approach
In total, 116 top management teams from the member of the Indonesian Advertising Association (P3I) were recruited for this study. The data was obtained through an online survey and analyzed using the PLS-structural equation modeling (SEM) technique.
Findings
This study revealed the importance of organizational learning and adaptive organization in minimizing technology disruption and enabler of the business model transformation. In an always-changing environment, the adaptive organization is the core element and catalyst of firm transformation. The acceleration of business model transformation is empowered through establishing an organization's learning system by exploiting existing knowledge, exploring new knowledge and cultivating a learning culture.
Practical implications
In today’s fast-paced digital world and a constant state of flux, advertising agencies need to build a sustainable business model and structure that allows them to be flexible, adaptive to changes and efficient.
Originality/value
To the best of the authors’ knowledge, this study was the first to develop a model to mitigate technology disruption and enable necessary elements to create a transformation business model.
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Paritosh Pramanik and Rabin K. Jana
This paper aims to discuss the suitability of topic modeling as a review method, identifies and compares the machine learning (ML) research trends in five primary business…
Abstract
Purpose
This paper aims to discuss the suitability of topic modeling as a review method, identifies and compares the machine learning (ML) research trends in five primary business organization verticals.
Design/methodology/approach
This study presents a review framework of published research about adopting ML techniques in a business organization context. It identifies research trends and issues using topic modeling through the Latent Dirichlet allocation technique in conjunction with other text analysis techniques in five primary business verticals – human resources (HR), marketing, operations, strategy and finance.
Findings
The results identify that the ML adoption is maximum in the marketing domain and minimum in the HR domain. The operations domain witnesses the application of ML to the maximum number of distinct research areas. The results also help to identify the potential areas of ML applications in future.
Originality/value
This paper contributes to the existing literature by finding trends of ML applications in the business domain through the review of published research. Although there is a growth of research publications in ML in the business domain, literature review papers are scarce. Therefore, the endeavor of this study is to do a thorough review of the current status of ML applications in business by analyzing research articles published in the past ten years in various journals.
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Transient climate sensitivity relates total climate forcings from anthropogenic and other sources to surface temperature. Global transient climate sensitivity is well studied, as…
Abstract
Transient climate sensitivity relates total climate forcings from anthropogenic and other sources to surface temperature. Global transient climate sensitivity is well studied, as are the related concepts of equilibrium climate sensitivity (ECS) and transient climate response (TCR), but spatially disaggregated local climate sensitivity (LCS) is less so. An energy balance model (EBM) and an easily implemented semiparametric statistical approach are proposed to estimate LCS using the historical record and to assess its contribution to global transient climate sensitivity. Results suggest that areas dominated by ocean tend to import energy, they are relatively more sensitive to forcings, but they warm more slowly than areas dominated by land. Economic implications are discussed.
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Feng Yao, Qinling Lu, Yiguo Sun and Junsen Zhang
The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the…
Abstract
The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.
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The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First…
Abstract
The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and not on matching or valuation tasks, though they depend on assumptions concerning the nature of probabilistic choice under risk. Second, estimated weighting functions contradict widely held priors of an inverse-s shape with fixed point well in the interior of the (0,1) interval: Instead the author usually finds populations dominated by “optimists” who uniformly overweight best outcomes in risky options. The choice pairs used here mostly do not provoke similarity-based simplifications. In a third experiment, the author shows that the presence of choice pairs that provoke similarity-based computational shortcuts does indeed flatten estimated probability weighting functions.
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Thalia Anthony, Juanita Sherwood, Harry Blagg and Kieran Tranter
Fatemeh Yaftiyan, Marziyeh Rassaf, Mohammadjafar Nikimaleki Borchalouei and Hamide Ghahremani
This chapter assists in Iran’s start-ups swift internationalisation from the onset. Indeed, it sheds in-depth qualitative and quantitative insights into analysing the propelling…
Abstract
This chapter assists in Iran’s start-ups swift internationalisation from the onset. Indeed, it sheds in-depth qualitative and quantitative insights into analysing the propelling factors towards entrepreneurial internationalisation. To accomplish this feat, a mixed method of Systematic Literature Review (SLR), Fuzzy-Delphi (FD) and Fuzzy-DEMATEL (Decision Making Trial and Evaluation Laboratory) – ISM (Interpretive Structural Modelling) – MICMAC (Matrix-based Multiplication Applied to a Classification) (FDIM), along with a multi-scenario analysis have innovatively been applied. As a result, entrepreneur characteristics and an accessible qualified workforce, even in foreign countries, are the most prominent drivers. Most probably, the institutional voids, interconnected benchmarking and the advent of new disruptive technologies form the independent factors which can sharply influence the whole system, particularly the entrepreneur characteristics as a dependent one. Moreover, social media, customer orientation and the domestic market cover autonomous drivers, which can moderately be affected or influence the abovementioned factors.
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