Development of a service quality scale for pharmaceutical supply chains

Ahmad, Niaz; Awan, Muhammad Usman; Raouf, A.; Sparks, Leigh

doi:10.1108/17506120910948494

Cited by 31 publications

(17 citation statements)

References 49 publications

(75 reference statements)

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“…Thus, the study has proposed a new scale, using inputs from literature and practitioners of small-medium manufacturing enterprises. The findings of this study are in alignment with those obtained by Ahmad et al (2009); Rodrigues et al (2011);Prakash (2014) and Parmata (2016). The proposed model embodies relationship among variables defined to co-create value for both provider and receiver and suggests facilitate planning and implementing of quality improvement programs towards the appraisal and performance evaluation of HR function in the organizations under study.…”

Section: Resultssupporting

confidence: 78%

Developing a scale to measure employee service quality in Indian SMEs

Gandhi¹,

Sachdeva²,

Gupta³

2018

10.5267/j.msl

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Section: Resultssupporting

confidence: 78%

Developing a scale to measure employee service quality in Indian SMEs

Gandhi¹,

Sachdeva²,

Gupta³

2018

10.5267/j.msl

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“…Other studies conducted in emerging economies have reported similar issues (e.g. Ahmad et al, 2009;Ali et al, 2012;Dubey & Gunasekaran, 2016;Jeswani et al, 2008;Kureshi et al, 2010;Ryan & Tipu, 2013;Singh et al, 2010). For example, Malik and Kotabe (2009) collected data from seven cities in India and Pakistan using convenience sampling, and could not find an up-to-date list of firms operating in each country.…”

Section: Data Collection Methodsmentioning

confidence: 94%

Determining the antecedents of dynamic supply chain capabilities

Aslam

Blome

Roscoe

et al. 2020

SCM

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Purpose The purpose of this paper is to determine the antecedents of dynamic supply chain capabilities (DSCCs). The authors test entrepreneurial orientation (EO) and supply chain learning orientation (SCLO) as two antecedents of DSCCs. Design/methodology/approach The paper uses structural equation modelling to test a hypothetical model. Data are gathered from a survey of 275 operations managers in Pakistan’s turbulent manufacturing industry. Findings The findings suggest that the weaker direct effects of EO, in comparison to the indirect effects, indicate that an SCLO mediates the relationship between EO and DSCCs. Research limitations/implications It is widely accepted that firms do not compete with each other, instead, it is end-to-end supply chains that fight for market dominance. Many scholars use the dynamic capabilities view to understand supply chain level competition. However, the dynamic capabilities view is firm-centric in its examination of how companies transform internal resources to compete in the external environment. The theoretical contribution of this paper is a roadmap of how to build dynamic, supply-chain level and capabilities by determining the key antecedents. This paper explains that DSCCs emerge when buyers and suppliers share strategic orientations. Firms with an EO and the ability to learn with supply chain partners are well-positioned to develop DSCCs. This provides a new angle to theory testing by indicating that dynamic capabilities are enabled by an EO and an ability to learn with supply chain partners. Practical implications Managers are given the building blocks of DSCCs, starting with fostering an entrepreneurially-oriented mindset in the company and then learning with supply chain partners. Entrepreneurially-oriented managers are encouraged to take risks and co-develop innovative ideas with suppliers during the supply chain learning process. Originality/value This study is one of the earliest efforts to determine the strategic orientations that antecede the emergence of DSCCs.

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“…The companies in capital have the potential to lobby to influence the MOH and Food and Drug Organization. [ 19 20 21 ]…”

Section: Discussionmentioning

confidence: 99%

Evaluation of productivity in Iranian pharmaceutical companies: A DEA-based Malmquist approach and panel data analysis

et al. 2015

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Objective:In this study, we aimed to assess comparative productivity of 21 pharmaceutical companies in Iran during 2000–2013.Methods:To evaluate the productivity trend of pharmaceutical companies in Iran, we used data envelopment analysis-based Malmquist index. “Total assets” and “capital stock” as inputs and “net sales” and “net profit” as outputs extracted from Tehran stock exchange, were selected to be included in the analysis. This method provides the possibility for analyzing the performance of each company in term of productivity changes over time. We also used an estimation generalized least square panel data model to identify the factors that might affect productivity of pharmaceutical companies in Iran using EViews 7 and Deep 2.1 software.Findings:The mean total productivity during all years of the study was 0.9829, which indicates the improvement in their overall productivity. The results, over the 13-year period, indicated that the range of productivity changes in pharmaceutical companies, that were included in this study, was between 0.884 and 1.098. Panel data model indicated that age of company could positively (t = 4.765978, P < 0.001) and being located in cities other than Tehran (the capital) could negatively (t = −5.369549, P < 0.001) affect the productivity of pharmaceutical companies. The analysis showed the new policy (brand-generic scheme) and also the type of ownership did not have a significant effect on the productivity of pharmaceutical companies.Conclusion:In this study, pharmaceutical productivity trends were fluctuated that could be due to the sub-optimal attention of policy makers and managers of pharmaceutical companies toward long-term strategic planning, focusing on productivity improvement.

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Development of a service quality scale for pharmaceutical supply chains

Cited by 31 publications

References 49 publications

Developing a scale to measure employee service quality in Indian SMEs

Developing a scale to measure employee service quality in Indian SMEs

Determining the antecedents of dynamic supply chain capabilities

Evaluation of productivity in Iranian pharmaceutical companies: A DEA-based Malmquist approach and panel data analysis

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