An integrated approach for evaluating lean innovation practices in the pharmaceutical supply chain

Meidute-Kavaliauskiene, Ieva; Cebeci, Halil Ibrahim; Ghorbani, Shahryar; Činčikaitė, Renata Article An integrated approach for evaluating lean innovation practices in the pharmaceutical supply chain Logistics Provided in Cooperation with: MDPI – Multidisciplinary Digital Publishing Institute, Basel Suggested Citation: Meidute-Kavaliauskiene, Ieva; Cebeci, Halil Ibrahim; Ghorbani, Shahryar; Činčikaitė, Renata (2021) : An integrated approach for evaluating lean innovation practices in the pharmaceutical supply chain, Logistics, ISSN 2305-6290, MDPI, Basel, Vol. 5, Iss. 4, pp. 1-17, https://doi.org/10.3390/logistics5040074 This Version is available at: https://hdl.handle.net/10419/310197 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may be saved and copied for your personal and scholarly purposes. You are not to copy documents for public or commercial purposes, to exhibit the documents publicly, to make them publicly available on the internet, or to distribute or otherwise use the documents in public. If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ logistics Article An Integrated Approach for Evaluating Lean Innovation Practices in the Pharmaceutical Supply Chain Ieva Meidute-Kavaliauskiene 1,* , Halil Ibrahim Cebeci 2, Shahryar Ghorbani 3and Renata ˇ Cinˇcikait˙ e1   Citation: Meidute-Kavaliauskiene, I.; Cebeci, H.I.; Ghorbani, S.; ˇ Cinˇcikait˙ e, R. An Integrated Approach for Evaluating Lean Innovation Practices in the Pharmaceutical Supply Chain. Logistics 2021,5, 74. https:// doi.org/10.3390/logistics5040074 Academic Editor: Robert Handfield Received: 17 August 2021 Accepted: 7 October 2021 Published: 13 October 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). 1Faculty of Business Management, Vilnius Gediminas Technical University, Sauletekio al. 11, 10223 Vilnius, Lithuania; [email protected] 2Department of Management Information System, University of Sakarya, Sakarya 54050, Turkey; [email protected] 3Department of Production Management, University of Sakarya, Sakarya 54050, Turkey; [email protected] *Correspondence: [email protected] Abstract: Backgroung: Lean innovation focuses on minimizing waste in the product development stages in order to increase productivity by obtaining customer feedback more quickly and efficiently. The usage of lean innovation practices in product development stages in the pharmaceutical supply chain is the topic of an increasing amount of research on the critical question of how lean innovation practices can be implemented in a pharmaceutical supply chain or logistic sector. To answer this question, we first identified lean innovation practices by reviewing the literature. Methods: the identified practices were screened using the fuzzy Delphi method (FDM). The expert panel included eight persons working in pharmaceutical supply chain fields. In the next step, the causal relationships between practices were analyzed using the Gray DEMATEL (GDEMATEL) technique. Results: show that technological knowledge was the most crucial factor in lean innovation practices in the pharmaceutical supply chain. Conclusions: Actualizing lean innovation in the supply chain is more than just utilizing the correct strategies and instruments. To execute lean innovation effectively, a reevaluation must be accomplished: A culture that recognizes requirements for change and is set up for consistent change is essential. Methodological strategies such as the value system cannot be set up as a one-time strategy. To execute lean innovation on a long-haul premise, members must be included and become acclimated to a proceeding with the progress process. Changes in forms are frequently used because of an absence of association of suppliers, regardless of whether measures are sensible. Keywords: lean innovation; lean innovation practice; prototyping; gray DEMATEL 1. Introduction As a vital and integral component of modern life, medicine is used to treat human and animal diseases [ 1 ]. Due to their different chemical structures and physical properties, research on and investigations into medicines face many challenges and issues [ 2 ]. Having experienced difficult conditions and undergone fluctuations over the past few decades, the pharmaceutical supply chain is now considered to be one of a country’s most essential and strategic industries [ 1 ]. Drug manufacturing and health logistics are attractive fields in which to study different strategies of commerce and innovation [ 1 ]. Currently, organizational transformation is the biggest issue facing firms, and innovation is vital to the survival of any organization. In addition, supply chain innovation provides an essential competitive advantage [ 3 ]. Innovation is a critical factor in the success of supply chains in line with economic progress and better access to commercial markets [ 4 ]. According to experts, innovative technologies play vital roles in countries’ economic growth and development. Research and development groups are key factors in the realization of such technologies [ 5 ]. Innovation is a way of creating value by developing new knowledge or Logistics 2021,5, 74. https://doi.org/10.3390/logistics5040074 https://www.mdpi.com/journal/logistics Logistics 2021,5, 74 2 of 17 using knowledge in new ways [ 6 ]. According to Peter Drucker, “innovation” is the only real competitive advantage for the organization. If a company can only have one great ability, it must be innovativeness [ 7 ]. Innovation is a prerequisite for success and survival and found its way through organizations around the world [ 6 ]. Data from Statista [ 8 ] suggest that expenditure on drug research and development will continue to grow worldwide. As of 2018, approximately USD 1.2 trillion has been spent on medicines, with an expected increase to USD 1.52 trillion by 2023. Furthermore, the total amount of medical waste was estimated to be worth USD 13.3 billion in 2020, which includes the high level of wastage associated with pharmaceuticals and contributes to an increase in the overall cost of healthcare [ 9 ]. The healthcare literature suggests that the adoption of improvement approaches and innovative interventions could enhance healthcare supply chains and help to reduce waste and provide improved services [10]. The success of knowledge-based organizations is guaranteed by innovation [ 11 ]. Lean innovations support the lean review of innovation, which is a relatively new concept that can be used to upgrade the innovation process [ 12 ]. Lean thinking has recently become the preferred management philosophy used by organizations to enhance operational performance. Although leanness has historically focused on well-structured processes, its focus has shifted towards less-structured processes with an innovative [ 13 ] and lean launch or startup [14]. The literature shows that lean innovation occurs incrementally when applied to R&D [ 6 ] or production processes [ 15 ]. According to Nicoletti (2018), lean innovation aims to reduce waste, improve effectiveness, reduce the time required to introduce new products into the market, minimize operating costs, and add value to customers [ 16 ]. Lean innovation enables organizations to turn their structural cultures into open and dynamic cultures that promote learning about and innovation of supply chains [ 17 ]. However, the number of publications on leanness and innovation remains limited [ 18 ]. The use of innovation in production is a new issue, particularly in the pharmaceutical industry. This leads to an analysis of the impact of lean innovation in a service context. In this study, the pharmaceutical supply chain was selected as a case study because this industry holds a strategic position in the world. The pharmaceutical industry is committed to finding sustainable solutions for the future to reduce negative environmental impacts and meet the highest ethical standards. The literature on pharmaceutical supply chains shows that the application of innovative techniques can reduce pharmaceutical waste, enhance the quality of healthcare services, improve the effectiveness of inventory control, increase supply chain innovativeness, and enhance the reliability of information. Similarly, from a practical perspective, reports have been published by healthcare institutes that aim to provide guidance to the healthcare supply chain on how best to implement lean innovative approaches to improve the delivery of medicines. However, the adequate implementation of lean innovation within the pharmaceutical supply chain has not yet been achieved; there appears to be a lack of experience and knowledge of how such initiatives should be implemented. The lack of focus on the combination of lean innovative practices that are considered to be the most effective ways to manage the pharmaceutical supply chain has been emphasized in the literature. Here, we attempt to make a rigorous and relevant contribution by considering both a theoretical and a practical problem when designing research questions and proposing contributions. This study makes an incremental contribution in the sense that we identify what knowledge already exists and further develop what is currently known. In light of the above discussion, the main problem we address in the present study is that of identifying the practical actions necessary for the implementation of lean innovation in the pharmaceutical industry. The current study was conducted for the purpose of identifying and assessing lean innovations in the pharmaceutical industry. Accordingly, we pose three questions by which to identify and prioritize the factors that influence the implementation of lean innovations in the pharmaceutical industry: Logistics 2021,5, 74 3 of 17 1. What are the practices of lean innovation in the pharmaceutical supply chain? 2. How are lean innovation practices prioritized in the pharmaceutical supply chain? 3. How are the cause-and-effect relationships of lean innovation practices implemented in the pharmaceutical supply chain? This article aims to achieve the goal and answer the posed questions in two sections. In the first section, critical factors in lean innovation practices in the pharmaceutical supply chain area are determined by reviewing the literature. In the second section, these practices are screened and localized using the Fuzzy Delphi method. Finally, these practices are assessed, and the innovation actions are prioritized using the gray DEMATEL technique. 2. Literature Review Innovation has been a subject matter of research projects for several years. In the past decade, the scientific literature has begun to report an affiliation between leanness and innovation. Hoppmann et al. (2011) stated that only 27 publications were found regarding lean-driven innovation. In these publications, general lean principles, such as “creating a price for the customer”, “thinking systematically”, “flowing and pulling” and “continuous improvement” [19], are frequently employed to guide the implementation of lean thinking. In a production context, Smeds [ 20 ] argued that reorganizing production in step with lean principles would trigger a techno-organizational modification towards a lean enterprise, with a brand-new structure, strategy, and culture. Within the analysis and development (R&D) domain, Schuh et al. (2011) discussed the merits of implementing lean thinking principles in innovation management to develop progressive methods and to achieve innovations [ 21 ]. Besides businesses, lean can additionally be applied within healthcare and pharmaceutical supply chains [22]. Schuh et al. (2011) outlined the idea that that the lean innovation system represents the systematic interpretation of lean thinking principles concerning innovation and development. There are various reasons behind the impact of lean on innovation [ 22 ]. Firstly, it analyzes the root-cause issues and provides a modern and constructive input for brandnew ideas. Secondly, it increases individuals’ autonomy and adaptability, resulting in their active role in solving issues and providing uninterrupted reflective values for learning and research. These merits attest to lean innovation’s role in making innovation processes more efficient [ 12 ]. Sonnenberg and Sehested (2011) further define lean innovation as a group of specific information sharing and innovation management techniques. Lean innovation can support access to information and information integration through unique mechanisms. Investigating the formation of these mechanisms and the advantages and risks involved in their implementation is undoubtedly rewarding. One major criticism is related to the competitive advantages of a company. According to critics, given their vital role as the company’s final target in its quest for innovation, competitive advantages should have a much larger share of the research literature [ 23 ]. This apparent failure of the lean management literature to provide material on ways to boost the competitiveness of companies may bring about adverse outcomes, such as demotivation on the part of employees who feel the time and effort taken to enhance innovation approaches has been in vain. The need for management support introduces another risk related to lean innovation [ 12 ]. The risk may also be created, and engaged customers within the innovation processes will increase the prospect of lean innovation. Nevertheless, it simultaneously displays the weakness of the business or the corporation to the customer. These negative aspects of lean innovation are not investigated and discussed in detail in the respective literature, making further investigation on the subject urgent. Generally speaking, retaining a competitive advantage in analysis and development needs not only an increase in effectiveness, but also in potency of R&D. Vital product differentiation must also be achieved through the preparation of resources. This is often the central objective of lean innovation by applying lean thinking principles to R&D management. Logistics 2021,5, 74 4 of 17 Within the given research constraints, innovations are made by internal R&D as a reaction to business restrictions, issues, and the core of the new application, the most innovation-demanding portion of the company [ 13 ]. Sehested and Sonnenberg (2011) provided their vision of lean, innovation, and lean Innovation as follows: “Working with lean means working systematically to eliminate all non-valueadding processes to obtain your goals with the least possible hard work. Innovation is about creating values by solving the problem. Furthermore, they see Innovation as the complex process of finding the solution to the situation that starts with imagination; nevertheless, the step that comes after creativity demands fast usage of available knowledge.” Radeka (2012) also claims that “the ability to innovate is merely worth something if those innovations generate values”. This indicates that lean is a necessary and even integral part of innovations made within an organization [24]. Unwinding the various guidelines of thought about lean innovation makes it possible to underline two general statements: 1. Lean innovation is a beneficial and compatible method for managing some critical corporate competitive resources. 2. Lean innovation has faced many barriers in implementation. Nevertheless, the difficulties may be projected by an individual company’s mode of business. We systematically analyzed the scientific and management literature in a wide selection of databases [25]. Gayialis et al. (2018) developed an advanced cloud-based vehicle routing and scheduling system for use in urban freight transportation. The scope of the paper was to describe the concept and methodological approach for the development of such a routing and scheduling system operating in a cloud environment. The definition of its requirements and the development of the system is the primary purpose of an ongoing research project, being in its first stages of the system’s analysis and design [26]. Touboulic et al. (2020) examined the relationship between critically engaged research and the process of theorizing in supply chain management (SCM). The essay presented an expanded model of knowledge production for the field of SCM. It explored opportunities for the demonstration of new knowledge types, emphasizing knowledge produced through a critical engagement with practice. They offered a discussion on how critically engaged research may be applied in SCM research to build, elaborate, and test theory [27]. Kechagias et al. (2020) analyzed the application of an urban freight transportation system to allow for reduced environmental emissions. An application of the system was performed for validation purposes, concerning the comparison of the system’s results with corresponding real-life data provided by a medium-sized logistics company. The testing results revealed its significant contribution to the reduction in the environmental impact of the company’s distribution services [28]. Yang et al. (2020) investigated the supplier selection for the adoption of green innovation in sustainable supply chain management practices in the Chinese textile manufacturing industry. The findings indicated that economic criteria were the most vital green innovation criteria. These findings will help managers, practitioners, and policymakers implement green innovation criteria in sustainable manufacturing supply chains [29]. Breen et al. (2020) carried out the management of pharmaceutical logistics to sustainability and beyond. Within pharmaceutical logistics, sustainability can mean business survival, addressing resource depletion, manufacturing conscientiously and responsibly, contributing to our economy, and doing no harm to our society and communities. Sustainability is a challenge in a supply chain that continues to grow organically, responding to changing patient needs, technological innovation, competition, political and regulatory governance, and austerity. This research highlights key areas of interest within the sustainability conversation as applied to pharmaceutical logistics [30]. Logistics 2021,5, 74 5 of 17 Argiyantari et al. (2020) investigated the literature review of pharmaceutical supply chain transformation by applying the lean principle. This study provides a systematic literature review that proposes an analysis and classification of the previous literature as falling within four categories: the supply chain area, research approach, research objective, and lean supply chain elements [31]. Bullón Pérez et al. (2020) investigated the traceability of ready-to-wear clothing through blockchain technology. The goal of the paper was to introduce more recent traceability schemes into the apparel industry together with the proposal of a framework for ready-to-wear clothing which allows transparency in the supply chain, clothing authenticity, reliability and integrity, and the validity of the retail final products to be ensured, as well as the validity of the elements that compose the whole supply chain [32]. Cannon et al. (2020) carried out out a study entitled “complements or conflicts: R&D and lean innovation approach”. Analysis of more than 850 firm years’ worth of data showed that the relationship between lean and R&D productivity is nonlinear, specifically an inverted U shape (concave). Leanness provided some early R&D productivity improvement benefits, but R&D productivity leveled then declined over time [33]. Talukder et al. (2021) designed a multi-indicator supply chain management framework for food convergent innovation in dairy logistics. The developed framework can serve as a decision support tool to evaluate and improve dairy logistics [34]. In her research, Florida-Benitez (2021) concluded that airport promotes an increase in the establishment of companies in the city and showed how this plays an essential role in the tourist, air cargo, and logistics development and Málaga’s local economy [ 35 ]. Additionally, in another study, she analyzed the effects of COVID-19 on airlines, airports, and the destination of Andalusia. On that basis, the study assessed the bankruptcy of some airlines, closure, the reduction in the frequency of air routes, COVID-19 measures at airports by governments, etc., to adapt to new circumstances, be efficient, and plan their resources according to the tourist demand [36]. Papalexi et al. (2021) analyzed the implementation of innovative plan within the pharmaceutical supply chain. The analysis led to the creation of the innovative pharmaceutical supply chain framework (IPSCF) that guides the healthcare system in how SCM problems could be solved using innovative approaches [37]. The trend of research on lean innovation management is growing (Figure 1). Figure 1. Research trend between 1997 and 2020. Out of the 83 sources reviewed, 47 percent were qualitative case studies, and 18 percent were conceptual research. Multi-method studies, surveys, systematic literature reviews, interviews, and content analyses constituted 14, 10, 8, 2, and 1%, respectively. Based on what has been discussed above, this study reviewed the literature by studying the lean innovation practices, which are the most essential practices, shown along with their sources in Table 1. Logistics 2021,5, 74 6 of 17 Table 1. Perspectives on lean innovation. Perspective on Lean Author(s) Types of Innovation Methodology Lean as process management/improvement initiative [38] Product innovation Quantitative (Survey) [39] Product and process innovation Theory-based Lean six sigma [40] Not distinguished Theory-based [22] Not central to the investigations Theory-based [41] Product and process innovation Qualitative (Interviews) Lean design and lean supply chain management [42] Not distinguished Quantitative (Survey) [43] Not distinguished Quantitative (Survey) Lean enterprise [44] Not central to the investigations Theory-based General lean attributes, principles, and aims [45] Not distinguished Theory-based [46] Not central to the investigations Theory-based [47] Product and process innovation Qualitative (Interviews) Lean innovation practice [48] Not clearly distinguished Qualitative (Questionnaire and Interviews) [49] Product innovation Qualitative (Questionnaire and Interviews) Each syndication was analyzed independently by the solitary designers in order to extract the various tools, methodologies, or organizational alternatives suggested in the materials for the lean transformation of operations’ innovation. Then, this group of tools and techniques was analyzed in a crisscross design to integrate the many perspectives found and create a construction that identifies the most internationally known elements of lean innovation [ 25 ]. This work reviewed 27 lean innovation practices, reported in Table 2. Table 2. Lean innovation practices. No. Practices References 1 Deep understanding of customer needs [12,50–53] 2 Early identification of production problems [12,50,51,54,55] 3 Integration of suppliers in the design and development process [18,51,55] 4 Modular design and reduction of components [18,51,53,55] 5 Supermarket of technical knowledge [18,51,53,55] 6 Generation of alternative product concept [51,53,55] 7 Systematic problem solving [18,50,51,53,55,56] 8 Heavyweight project leader [18,51–53,55,56] 9 Integrated team of responsible experts [18,50–53,55] 10 Visual project board [12,18,51,52] 11 Visual pull planning [12,18,50,52,53] 12 Integration events [18,51–53,57] 13 One-piece flow in the daily work [12] 14 Working on a single project [51,52,57] 15 Project portfolio [12,57] 16 One-piece flow in the project portfolio [12,18,57] 17 Integrated problem solving [57] 18 Anticipated prototyping [18,53] 19 Value stream mapping [52,53] 20 Road mapping for technologies [12] 21 Project added value [12,18,51,52] 22 Product design style [12,18,50,52,53] 23 Design management [18,51–53,57,58] 24 Optimization of the event processes [12] 25 High dependableness of IT systems [12,18,51,52] 26 Use standardized controlling charts [12,18,57] 27 Innovation dominant supported [57] Logistics 2021,5, 74 7 of 17 3. Methodology This research utilized the Fuzzy Delphi method to explore the lean innovation practice. Another technique used herein was gray DEMATEL, which is useful for calculating the cause-and-effect relationships between lean innovation practices. To ascertain the analysis gap, we tended to conduct a scientific search for articles in communicative journals. The bibliographical databases searched include Science Direct, Springer, Emerald, Taylor and Francis, Wiley, Google Scholar, and Scopus. This search confirmed that no study was published thus far with a spotlight on lean innovation practice. The data for this research were collected through many sources: depository data, including organization guidance, books and documents, and interviews with experts. Within the information assortment method, an expert team of eight specialists was assembled; their backgrounds are shown in Table 3. Table 3. Background of experts. Expert ID Specialty Positions Work Experience (Years) 1 R&D Chief 14 2 Industries MD 22 3 HR Chief 18 4 R&D MD 11 5 Industries MD 19 6 Management MD 21 7 Assurance quality Chief 18 8 Management Production manager 26 The experts selected for the panel were chosen due to their expertise and position in their organizations. Attributable to the beta nature of this analysis, the authors used qualitative information assortment strategies, specifically semi-structured interviews, as they supply a more prosperous information supply than quantitative strategies. When finalizing the expert panel, we began the information assortment method. Finally, the experts’ responses were collected. Data gathering tools included a literature review, semistructured interviews, and a questionnaire. The primary tool was used to uncover an initial associated set of lean innovation practices. The methodology framework is shown in Figure 2. 3.1. The Fuzzy Delphi Method Dalkey and Helmer developed the Delphi method, and Helmer developed the Delphi method in 1963 [ 59 ]. This technique is similar to the experts’ opinion survey technique, with 3 essential characteristics: anonymous response, iteration and controlled feedback, and applied math cluster response. In several real situations, experts’ judgment cannot be exactly given quantitative values and crisp information area unit is meagre in comparison to model natural systems thanks to the unclearness, inexactitude, and subjective nature of human thinking and the subjective nature of human thinking and judgment and preferences. Due to this, fuzzy numbers was suggested by Zadeh as a robust tool to beat these drawbacks [ 60 ]. Initially designed by Ishikawa, the fuzzy Delphi method (FDM) is a combination of fuzzy pure mathematics and the Delphi method. The steps of the FDM area unit are as follows [61–64]: Step 1: Distinguishment of the analysis criteria associated with the study. First, the attainable criteria ought to be found through a careful literature review. Step 2: Collection of expert opinions through a mistreatment call cluster. After distinguishing relevant performance criteria, consultants associated with the analysis area unit were invited to work out the importance of the known criteria through the mistreatment of the linguistic variables conferred in Table 4. Logistics 2021,5, 74 8 of 17 Figure 2. Research framework. Table 4. Linguistic scales. Linguistic Term Fuzzy Number Very low (VL) (0, 0, 0.25) Low (L) (0, 0.25, 0.5) Medium (M) (0.25, 0.5, 0.75) High (H) (0.5, 0.75, 1) Very high (VH) (0.75, 1, 1) Step 3: Identification of necessary criteria. The final step within the FDM is to characterize the necessary criteria, which is finished by scrutinizing the burden of every criterion with the threshold’S ~ . The value of S ~ is calculated by the type of all criteria weights. In this regard, we should always find the (TFNs) τfor every criterion, as outlined in (1)–(5). eaij =aij,bij,cijfor i=1, . . . , n,j=1, . . . , m(1) e τj=aj,bj,cj(2) aj=minaij(3) bj=∏n i=1bij1 n(4) Logistics 2021,5, 74 15 of 17 incline guideline and/or hone can uniquely clarify more variation in a firm’s innovativeness than the displayed integrator demonstrate does. 6.2. Limitation and Future Study This research stated potential implications for logistics theory and practice. While the study itself gives insights into the factors that might affect the pharmacies’ lean innovativeness, it more information is needed. A more reliable study could be carried out. This research’s theoretical perspective also generates another avenue of future research, which would be to target and examine the performance of pharmacies’ logistics where lean innovative approaches, such as RL practices, have been considered and implemented. As the current study focused on lean practices in developing countries, researchers are encouraged to investigate the aspects of the pharmacies’ logistics adopted across European boundaries. Author Contributions: Conceptualization, I.M.-K. and H.I.C.; formal analysis, H.I.C. and R. ˇ C.; investigation, I.M.-K. and S.G.; methodology, H.I.C. and S.G.; resources, R. ˇ C.; software, H.I.C.; supervision, I.M.-K.; validation, I.M.-K. and R. ˇ C.; visualization, S.G. and R. ˇ C.; writing—original draft, H.I.C. and S.G.; writing—review and editing, I.M.-K. and R. ˇ C. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data of this study are available from the authors upon request. Conflicts of Interest: The authors declare no conflict of interest. References 1. Sayadi, M.H.; Trivedy, R.K.; Pathak, R.K. Pollution of pharmaceuticals in environment. I Control Pollut. 2010,26, 89–94. 2. Mompelat, S.; Le Bot, B.; Thomas, O. Occurrence and fate of pharmaceutical products and by-products, from resource to drinking water. Environ. Int. 2009,35, 803–814. [CrossRef] [PubMed] 3. Tseng, M.-L.; Wang, R.; Chiu, A.S.F.; Geng, Y.; Lin, Y.H. Improving performance of green innovation practices under uncertainty. J. Clean. Prod. 2013,40, 71–82. [CrossRef] 4. Bai, C.; Sarkis, J. A grey-based DEMATEL model for evaluating business process management critical success factors. Int. J. Prod. Econ. 2013,146, 281–292. [CrossRef] 5. Ivan, M.V.; Iacovoiu, V.B. Innovation and research and development important factors related to the nations competitiveness: The case of european economies. Commun. IBIMA 2009,10, 110–118. 6. Gong, Y.; Janssen, M. Demystifying the benefits and risks of Lean service innovation: A banking case study. J. Syst. Inf. Technol. 2015,17, 364–380. [CrossRef] 7. Heindl, D.J. Innovation Infrastructure. System Approach to Building an Innovation Organization; NTH Degree Software: Evanston, IL, USA, 2008. 8. Abdallah, K.; Huys, I.; Claes, K.; Simoens, S. Methodological Quality Assessment of Budget Impact Analyses for Orphan Drugs: A Systematic Review. Front. Pharmacol. 2021,12, 215. [CrossRef] 9. Papalexi, M.; Bamford, D.; Breen, L. Key sources of operational inefficiency in the pharmaceutical supply chain. Supply Chain Manag. Int. J. 2020,25, 617–635. [CrossRef] 10. Ponsignon, F.; Davies, P.; Smart, A.; Maull, R. An in-depth case study of a modular service delivery system in a logistics context. Int. J. Logist. Manag. 2021,32, 872–897. [CrossRef] 11. Rogers, E.M. Diffusion of Innovations; Free Press: New York, NY, USA, 2003; Volume 551. 12. Sehested, C.; Sonnenberg, H. Lean Innovation: A Fast Path from Knowledge to Value; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2010; ISBN 3642158951. 13. Karakulin, R. Lean Innovation in Large Companies: A Case of Implementation in R&D. Master’s Thesis, Lappeenranta University of Technology, Lappeenranta, Finland, 2015. 14. Ries, E. The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses; Currency: New York, NY, USA, 2011; ISBN 0307887898. 15. Cherrafi, A.; Elfezazi, S.; Govindan, K.; Garza-Reyes, J.A.; Benhida, K.; Mokhlis, A. A framework for the integration of Green and Lean Six Sigma for superior sustainability performance. Int. J. Prod. Res. 2017,55, 4481–4515. [CrossRef] Logistics 2021,5, 74 16 of 17 16. Ocampo, L.; Bongo, M.; Alinsub, J.; Casul, R.A.; Luar, M.; Panuncillon, N. Public service quality evaluation with SERVQUAL and AHP-TOPSIS: A case of Philippine government agencies. Socio-Econ. Plan. Sci. 2019,68, 100604. [CrossRef] 17. Bhasin, S. Performance of organisations treating lean as an ideology. Bus. Process Manag. J. 2011,17, 986–1011. [CrossRef] 18. Hoppmann, J.; Rebentisch, E.; Dombrowski, U.; Zahn, T. A framework for organizing lean product development. Eng. Manag. J. 2011,23, 3–15. [CrossRef] 19. Shingo, P. The Shingo Prize for Operational Excellence Model & Application Guidelines; Utah State University: Logan, UT, USA, 2012. 20. Smeds, R. Managing change towards lean enterprises. Int. J. Oper. Prod. Manag. 1994,14, 66–82. [CrossRef] 21. Schuh, G.; Lenders, M.; Hieber, S. Lean Innovation–Introducing value systems to product development. Int. J. Innov. Technol. Manag. 2011,8, 41–54. [CrossRef] 22. Johnstone, C.; Pairaudeau, G.; Pettersson, J.A. Creativity, innovation and lean sigma: A controversial combination? Drug Discov. Today 2011,16, 50–57. [CrossRef] 23. Arlbjørn, J.S.; Freytag, P.V. Evidence of lean: A review of international peer-reviewed journal articles. Eur. Bus. Rev. 2013 ,25, 174–205. [CrossRef] 24. Radeka, K. The Mastery of Innovation: A Field Guide to Lean Product Development; CRC Press: Boca Raton, FL, USA, 2012; ISBN 1439877025. 25. Biazzo, S.; Panizzolo, R.; de Crescenzo, A.M. Lean management and product innovation: A critical review. In Understanding the Lean Enterprise; Springer: Cham, Switzerland, 2016; pp. 237–260. 26. Gayialis, S.P.; Konstantakopoulos, G.D.; Papadopoulos, G.A.; Kechagias, E.; Ponis, S.T. Developing an advanced cloud-based vehicle routing and scheduling system for urban freight transportation. In Proceedings of the IFIP International Conference on Advances in Production Management Systems, Seoul, Korea, 26–30 August 2018; pp. 190–197. 27. Touboulic, A.; McCarthy, L.; Matthews, L. Re-imagining supply chain challenges through critical engaged research. J. Supply Chain Manag. 2020,56, 36–51. [CrossRef] 28. Kechagias, E.P.; Gayialis, S.P.; Konstantakopoulos, G.D.; Papadopoulos, G.A. An application of an urban freight transportation system for reduced environmental emissions. Systems 2020,8, 49. [CrossRef] 29. Yang, Y.; Wang, Y. Supplier selection for the adoption of green innovation in sustainable supply chain management practices: A case of the chinese textile manufacturing industry. Processes 2020,8, 717. [CrossRef] 30. Breen, L.; Papalexi, M.; Xie, Y. Managing the Pharmaceutical Supply Chain—To Sustainability and Beyond. In Global Pharmaceutical Policy; Springer: Berlin/Heidelberg, Germany, 2020; pp. 29–52. 31. Argiyantari, B.; Simatupang, T.M.; Basri, M.H. Pharmaceutical supply chain transformation through application of the Lean principle: A literature review. J. Ind. Eng. Manag. 2020,13, 475–494. [CrossRef] 32. Bullón Pérez, J.J.; Queiruga-Dios, A.; Gayoso Martínez, V.; Martín del Rey, Á. Traceability of ready-to-wear clothing through blockchain technology. Sustainability 2020,12, 7491. [CrossRef] 33. Cannon, A.; John, C.S.T. Complements Or Conflicts: R&D And Lean Innovation Approaches. Int. J. Innov. Manag. 2021 ,25, 2150042. 34. Talukder, B.; Agnusdei, G.P.; Hipel, K.W.; Dubé, L. Multi-indicator supply chain management framework for food convergent innovation in the dairy business. Sustain. Futures 2021,3, 100045. [CrossRef] 35. Florido-Benítez, L. How Málaga’s airport contributes to promote the establishment of companies in its hinterland and improves the local economy. Int. J. Tour. Cities 2021. [CrossRef] 36. Florido-Benítez, L. The effects of COVID-19 on Andalusian tourism and aviation sector. Tour. Rev. 2021,76, 829–857. [CrossRef] 37. Papalexi, M.; Bamford, D.; Nikitas, A.; Breen, L.; Tipi, N. Pharmaceutical supply chains and management innovation? Supply Chain Manag. Int. J. 2021. [CrossRef] 38. Jones, J.L.S.; Linderman, K. Process management, innovation and efficiency performance: The moderating effect of competitive intensity. Bus. Process Manag. J. 2014,20, 335–358. [CrossRef] 39. Berente, N.; Lee, J. How process improvement efforts can drive organisational innovativeness. Technol. Anal. Strateg. Manag. 2014 , 26, 417–433. [CrossRef] 40. Byrne, G.; Lubowe, D.; Blitz, A. Using a Lean Six Sigma approach to drive innovation. Strateg. Leadersh. 2007 ,35, 5–10. [CrossRef] 41. Antony, J.; Setijono, D.; Dahlgaard, J.J. Lean Six Sigma and Innovation–an exploratory study among UK organisations. Total Qual. Manag. Bus. Excell. 2016,27, 124–140. [CrossRef] 42. Singh, S.K.; Goh, M. Multi-objective mixed integer programming and an application in a pharmaceutical supply chain. Int. J. Prod. Res. 2019,57, 1214–1237. [CrossRef] 43. Taylor, S.; Celuch, K.; Goodwin, S. The importance of brand equity to customer loyalty. J. Prod. Brand Manag. 2004 ,13, 217–227. [CrossRef] 44. Chen, H.; Lindeke, R.R.; Wyrick, D.A. Lean automated manufacturing: Avoiding the pitfalls to embrace the opportunities. Assem. Autom. 2010,30, 117–123. [CrossRef] 45. Alberts, C.; Dorofee, A.; Stevens, J.; Woody, C. Introduction to the OCTAVE Approach; Carnegie Mellon University: Pittsburgh, PA, USA, 2003. 46. Browning, T.R.; Sanders, N.R. Can innovation be lean? Calif. Manage. Rev. 2012,54, 5–19. [CrossRef] Logistics 2021,5, 74 17 of 17 47. Weber, S. Can Innovation Be Lean? Lean’s Influence on Innovation. Available online: https://www.semanticscholar.org/paper/ Can-Innovation-be-lean-Lean%E2%80%99s-Influence-on-Weber/27974be90c02feb7095836b25124f31581e2db17 (accessed on 10 October 2020). 48. Borrèl, C.A. The Effects of Lean Management on the Tension between Exploration and Exploitation in SMEs; University of Twente: Enschede, The Netherlands, 2013. 49. Siemerink, M.G.J. The Effects of Lean Management on Organizational Structure and the Type of Innovations Influenced by This Structure; University of Twente: Enschede, The Netherlands, 2014. 50. Haque, B.; James-Moore, M. Applying lean thinking to new product introduction. J. Eng. Des. 2004,15, 1–31. [CrossRef] 51. Morgan, J.M.; Liker, J.K. The Toyota Product Development System: Integrating People, Process, and Technology; Productivity Press: New York, NY, USA, 2020; ISBN 0367805154. 52. Oppenheim, B.W. Lean product development flow. Syst. Eng. 2004,7, 352–376. [CrossRef] 53. Schipper, T.; Swets, M. Innovative Lean Development: How to Create, Implement and Maintain a Learning Culture Using Fast Learning Cycles; CRC Press: Boca Raton, FL, USA, 2012; ISBN 1420093010. 54. Karlsson, C.; Ahlström, P. The difficult path to lean product development. J. Prod. Innov. Manag. 1996,13, 283–295. [CrossRef] 55. Ward, A.C.; Sobek, D.K., II. Lean Product and Process Development; Lean Enterprise Institute Inc.: Cambridge, MA, USA, 2007. 56. Baines, T.; Lightfoot, H.; Williams, G.M.; Greenough, R. State-of-the-art in lean design engineering: A literature review on white collar lean. Proc. Inst. Mech. Eng. Part B J. Eng. Manuf. 2006,220, 1539–1547. [CrossRef] 57. Reinertsen, D.; Bellinson, T. The Principles of Product Development Flow: Second Generation Lean Product Development; Lean Enterprise Institute Inc.: Cambridge, MA, USA, 2014. 58. Arab, A.; Sahebi, I.G.; Alavi, S.A. Assessing the key success factors of knowledge management adoption in supply chain. Int. J. Acad. Res. Bus. Soc. Sci. 2017,7, 2222–6990. [CrossRef] 59. Habibi, A.; Jahantigh, F.F.; Sarafrazi, A. Fuzzy Delphi Technique for Forecasting and Screening Items. Asian J. Res. Bus. Econ. Manag. 2015,5, 130–143. [CrossRef] 60. Habibi, A.; Sarafrazi, A.; Izadyar, S. Delphi Technique Theoretical Framework in Qualitative. Int. J. Eng. Sc. 2014,3, 8–13. 61. Ghasemian Sahebi, I.; Arab, A.; Sadeghi Moghadam, M.R. Analyzing the barriers to humanitarian supply chain management: A case study of the Tehran Red Crescent Societies. Int. J. Disaster Risk Reduct. 2017,24, 232–241. [CrossRef] 62. Sahebi, I.G.; Masoomi, B.; Ghorbani, S. Expert oriented approach for analyzing the blockchain adoption barriers in humanitarian supply chain. Technol. Soc. 2020,63, 101427. [CrossRef] 63. Sahebi, I.; Masoomi, B.; Ghorbani, S.; Uslu, T. Scenario-based designing of closed-loop supply chain with uncertainty in returned products. Decis. Sci. Lett. 2019,8, 505–518. [CrossRef] 64. Mohaghar, A.; Sahebi, I.G.; Arab, A. Appraisal of Humanitarian Supply Chain Risks Using Best-Worst Method. Int. J. Soc. Behav. Educ. Econ. Bus. Ind. Eng. 2017,11, 292–297. 65. Meidute-Kavaliauskiene, I.; Davidaviciene, V.; Ghorbani, S.; Sahebi, I.G. Optimal Allocation of Gas Resources to Different Consumption Sectors Using Multi-Objective Goal Programming. Sustainability 2021,13, 5663. [CrossRef] 66. Mahdiraji, H.A.; Zavadskas, E.K.; Arab, A.; Turskis, Z.; Sahebi, I.G. Formulation of manufacturing strategies based on an extended swara method with intuitionistic fuzzy numbers: An automotive industry application. Transform. Bus. Econ. 2021,20, 346–374. 67. Sahebi, I.G.; Toufighi, S.P.; Karakaya, G.; Ghorbani, S. An intuitive fuzzy approach for evaluating financial resiliency of supply chain. OPSEARCH 2021, 1–22. [CrossRef] 68. Arab, A.; Sahebi, I.G.; Modarresi, M.; Ajalli, M. A Grey DEMATEL approach for ranking the KSFs of environmental management system implementation (ISO 14001). Calitatea 2017,18, 115. 69. Lasagni, A. Intangible assets and firm heterogeneity: Evidence from Italy. Res. Policy 2014,43, 202–213. 70. Mahanty, C.; Mishra, B.K. Medical data analysis in eHealth care for industry perspectives: Applications. In An Industrial IoT Approach for Pharmaceutical Industry Growth; Elsevier: Amsterdam, The Netherlands, 2020; pp. 305–335. 71. Zhang, Q.; Li, Y.; Li, H.; Wang, G.; Chen, S. Study on the Impacts of the LNG Market Reform in China using a SVM based Rolling Horizon Stochastic Game Analysis. Energy Procedia 2017,105, 3850–3855. [CrossRef]