Why are research and practice on operational excellence still far apart? Ecological knowledge management view

Figures & data

Table 1. Some recent research on OE (works published in the last three years – from 2018 on).

Reference	Objective	Method	Findings
Edgeman (2018)	To explore the theoretical underpinnings for OE models.	Management theory, systems theory and excellence modeling were integrated to yield a complex management system based on OE model. Correspondence of this model with the Shingo OE model was explored.	Understanding the theoretical underpinnings of excellence models (i.e. elements, interactions and synergies) enabled the adaptation of such models to specific enterprise contexts, and course corrections whenever needed.
Found et al. (2018)	To clarify OE’s meaning and identify the underpinning theories and laws, or rules that guide it.	Based on a literature synthesis of the literature, OE theories are reviewed according to five criteria.	There have been many studies on the identification of common practices and regularities of OE, but there is no single underlying theory that meets the criteria for a good theory.
Sriyakul et al. (2019)	To examine the role of commitment to change to expediate supply chain OE.	Data from 190 Indonesian supply chain companies were collected. These data were analyzed with the help of PLS3.	Cultural traits, transformational leadership and commitment to change has a positive role in supply chain OE. Indonesian companies should adopt good organizational change strategies to increase excellence in their operations.
Sony (2019)	To investigate how to implement a sustainable OE initiative in the organization.	The study built a model for sustainability of OE considering the social, economic and environmental aspects.	Through the proposed model of sustainability, organizations will be able to implement OE initiatives.
Carvalho et al. (2019)	To propose the research questions that will help to understand the relationships and integration between the concepts of OE, organizational agility, and culture.	Through a literature review, the relationships of OE with both organizational culture and agility have been hypothesized.	These perceived limitations of OE initiatives, catalyzed by times of rapid change at the social and technical level, have motivated a new perspective that tackles the lack of sustainability in OE and the ability of its initiatives to promote continuing success.
Gólcher-Barguil et al. (2019)	To propose indicators to isolate the impact of manufacturing fluctuation and identify the payback of OE initiatives through cost benefits of achieving higher efficiency and yield.	A conceptual and mathematical development of the proposed indicators are presented, and validated through industrial applications.	The proposed indicators provide an effective cost-benefit analysis of OE. This contributes with more complete information regarding the performance of organizational processes, allowing better decision-making processes.
Dev et al. (2020)	To propose a roadmap to OE for sustainable reverse supply chain/logistics by the joint implementation of principles of Industry 4.0 and ReSOLVE model of circular economy approaches.	The connection between Industry 4.0 and circular economy was unveiled by addressing the case-based model affecting the economic and environmental performances.	Given the Industry 4.0 and circular capabilities, it is necessary to focus on the cost of the socially influenced operations involving factors such as collection investment and size of the end-user market that governs the product returns.
Moktadir et al. (2020)	To examine how to perform the practices of OE towards sustainability in industries.	The identified indicators were segregated into six dominant categories and 27 sub-indicators in the field of leather products industry. Their prioritization was established by adopting the best-worst method, involving simple pairwise comparison matrices compared with other multicriteria decision-making techniques.	Management indicators were at the highest priority. It is anticipated that the results originated from the study support the appropriate recognition of the significant indicators and drop the insignificant ones for successful OE towards sustainability practices in the supply chain of the emerging economy.
Bag et al. (2020)	To evaluate the role of big data analytics capability as an OE approach in improving sustainable supply chain performance.	Surveyed 520 executives in South Africa and received 520 valid responses. Partial Least Squares Structural Equation Modeling was used to analyze the data.	Big data analytics management capabilities have a significant effect on innovative green product development and sustainable supply chain outcomes. Big data analytics talent capabilities have a weaker but still significant impact on employee development and sustainable supply chain outcomes.
McDermott et al. (2021)	To explore the use of OE methodologies in the era of COVID-19.	A qualitative approach was utilized by interviewing a panel of leading academics and practitioners who are familiar with OE methodologies.	OE methodologies are proven and can be utilized in pandemic situations to improve efficiency in the healthcare system and preparedness for pandemics.
Tortorella et al. (2021a)	To examine the OE’s concept in the Fourth Industrial Revolution.	Conduction of interviews with experts, focusing on the shifts in OE’s concepts implied by the Industry 4.0 with regards to people, partnerships, processes, and products and services.	Although some attributes may remain the same, the emphasis of OE in the Fourth Industrial Revolution is likely to change. As interconnectivity and cyber-physical systems gain prominence, a more integrative and systemic perspective of OE is facilitated, expanding its meaning and understanding.

Figure 1. Conceptual model of the investigated ecological knowledge environment.

Table 2. Profiles of the interviewed experts.

Expert		Experience	Country	Socioeconomic context	Role	Organization characteristics^a,b
Academics	A1	10 years	Chile	Emerging	Associate Professor in Industrial Engineering	Large private university ranked among the top two hundred in the world
	A2	26 years	Brazil		Associate Professor in Industrial Engineering	Large private university ranked among the top seven hundred in the world
	A3	11 years	China		Full Professor in Industrial Engineering	Large public university ranked among the top six hundred in the world
	A4	25 years	India		Associate Professor in Operations and Supply Chain Management	Large private university ranked among the top five hundred in the world
	A5	22 years	Argentina		Full Professor in Operations Management	Large private university ranked among the top four hundred in the world
	A6	15 years	Mexico		Associate Professor in Industrial and Systems Engineering	Large public university ranked among the top seven hundred in the world
	A7	16 years	Spain	Developed	Full Professor in Engineering Management	Large public university ranked among the top six hundred in the world
	A8	14 years	USA		Associate Professor in Operations and Supply Chain Management	Large public university ranked among the top five hundred in the world
	A9	17 years	Italy		Associate Professor in Systems Engineering	Large private university ranked among the top two hundred in the world
	A10	21 years	UK		Full Professor in Industrial Engineering	Large private university ranked among the top one hundred in the world
	A11	12 years	Australia		Associate Professor in Operations and Supply Chain Management	Large public university ranked among the top one hundred in the world
	A12	18 years	New Zealand		Full Professor in Operations and Supply Chain Management	Large public university ranked among the top one hundred in the world
Practitioners	P1	22 years	Mexico	Emerging	Continuous Improvement Manager	Large multinational metal-mechanics manufacturer
	P2	15 years	Uruguay		Plant Manager	Large multinational auto parts manufacturer
	P3	20 years	South Africa		Industrial Director	Large multinational food manufacturer
	P4	25 years	Brazil		Facility and Maintenance Manager	Large multinational automotive manufacturer
	P5	18 years	Brazil		Supply Chain Manager	Large multinational metal-mechanics manufacturer
	P6	17 years	India		Engineering Director	Large multinational pharmaceutical manufacturer
	P7	21 years	Australia	Developed	Plant Manager	Large multinational aviation manufacturer
	P8	18 years	UK		Manufacturing Director	Large multinational food manufacturer
	P9	24 years	USA		Supply Chain Manager	Large multinational electronics manufacturer
	P10	28 years	Spain		Engineering Director	Large multinational equipment manufacturer
	P11	17 years	Italy		Engineering Manager	Large multinational food manufacturer
	P12	26 years	USA		Quality Director	Large multinational auto parts manufacturer
	P13	22 years	Germany		Continuous Improvement Manager	Large multinational tobacco manufacturer

Notes: ^aUniversity with more than 15,000 students; ^bManufacturer with more than 500 employees.

Table 3. Interviewees’ perceptions on the relationship between OE’s research and practice.

Socioeconomic context	Background	Strengths	Weaknesses	Opportunities	Threats
Emerging economies	Academics	‘We have developed collaboration with iconic manufacturing companies that may serve as an example for others.’ ‘Our academics have been pushed to develop industry-oriented research. This is now part of their key performance indicators.’	‘The knowledge we develop through our research on OE is mostly shared through articles publication. Practitioners are not used to read articles.’ ‘Many academics have never stepped on a shopfloor. They have gone through their careers oblivious to the real manufacturing problems.’	‘I believe our research should somehow merge the short term needs from manufacturers with the cutting-edge and long-term requirements from a truly theoretical contribution.’ ‘I think we could work in the fundamentals of our research activities. New PhD students must be reinforced to develop their research with an industry-oriented focus’	‘Manufacturers are mostly focused on their daily activities. They are running after short term goals, which impairs from thinking ahead.’ ‘Conferences on OE are supposed to be a place for knowledge exchange between practice and research. However, the conferences that we attend only have academics.’
	Practitioners	‘Researchers can sometimes provide solutions to highly complex problems at a much lower cost than a consulting firm would.’ ‘Our department of continuous improvement is constantly approaching the local researchers to discuss new techniques and checking how to incorporate them into our processes.’	‘We are not aware of what researchers have been developing on OE.’ ‘I feel that we do not fully benefit from the research on OE as we could. Most knowledge exchange and benchmarking in OE are done with other practitioners and companies.’	‘We must foster research activities as part of our business strategy. We even have some tax benefits if we invest on research. We seem to forget this opportunity.’ ‘The shopfloor must be seen as a huge laboratory. All research experiments should be conducted there. We must embrace this concept so that research and practice in OE can go hand in hand.’	‘Research usually takes a long time. In our scenario (manufacturing company), we need faster solutions. Customers and competitors do not wait.’ ‘Sometimes, academics seem to speak a different language. It is hard to communicate with them.’
Developed economies	Academics	‘Many research centers are funded by organizations, whose operational problems and difficulties are addressed and prioritized as part of the research activities of academics.’ ‘Most of our alumni (former PhD students) are working in the manufacturing industry playing leadership roles, which suggests that the knowledge they acquire in the academia is highly valued by practitioners.’	‘Confidentiality agreements with industry undermine the development of further studies in OE as well as the dissemination of the learning.’ ‘Openness to research is still an issue in many manufacturing companies. At the same time, researchers tend to find much more comfortable to stay in their offices.’	‘With the advent of new digital technologies from the Industry 4.0, there are many opportunities for developing conjoint projects with industry, since both academics and practitioners are learning about them.’ ‘Although publications are still one of our main performance indicators, journals have been valuing the submission of applied studies, which reinforces the close collaboration with industry.’	‘Most of the problems that practitioners face does not provide enough novelty to justify the development of a research in OE.’ ‘Practitioners often confuse research activities with consulting activities, leading to misaligned expectations.’
	Practitioners	‘Highly complex issues, that we usually lack skills, time and knowledge to solve them, are often shared with academics who we have been collaborating with.’ ‘Although we are a manufacturing company, we have a strong orientation to research and development. This can be observed in our products, processes and services.’	‘Many of the technical solutions suggested by research in OE are not feasible or practical to be implemented in our company. Those solutions are very far from our reality.’ ‘There seems to be a delay/mismatch between the research and practice in OE. The concepts studied today are not applicable today.’	‘The incoming workforce (millennials and post-millennials) is increasingly skilled. This can help to increase the value of research activities within our company.’ ‘We are reaching levels of competitiveness in which the value of research and innovation can no longer be overlooked. We need to strongly collaborate with researchers to stay ahead in the market.’	‘Researchers are mainly interested in publications. Industry needs more than good journal articles. We need actual solutions.’ ‘The responsiveness in academia is different from industry. We must provide rapid responses in a constantly changing scenario, while academics are more long-term oriented.’

Table 4. Commonalities in the relationship between OE’s research and practice according to KM activities.

KM activity	Strengths					Weaknesses					Opportunities					Threats
	Aspects	AEE	PEE	ADE	PDE	Aspects	AEE	PEE	ADE	PDE	Aspects	AEE	PEE	ADE	PDE	Aspects	AEE	PEE	ADE	PDE
Knowledge creation	Increasing incentives for industry-oriented research	N	N	++	+	Little awareness on what is being done	+	++	N	N	Digital transformation motivation	N	+	++	+	Different focus between short- and long-term activities	++	N	+	+
Knowledge retrieval	Recruitment of researchers as part of the industry workforce	N	N	++	+	Poor systematics for dissemination of learning	+	+	+	+	Development of industry-oriented PhDs	++	N	+	N	Misalignment in the form of knowledge registration	++	N	N	+
Knowledge transfer	Revision of academics’ performance indicators	++	N	+	N	Confidentiality agreements limitations	+	N	++	N	Highly skilled incoming workforce	N	+	N	++	Miscommunication and terminology issues	N	++	++	N
Knowledge application	Appreciation of the relationship between research and practice to solve complex problems	+	+	+	+	Lack of empathy	++	N	++	++	High competitiveness requirements	N	+	+	++	Different responsiveness levels	+	+	N	++

Notes: AEE: Academics from emerging economies; PEE: Practitioners from emerging economies; ADE: Academics from developed economies; PDE: Practitioners from developed economies; N: ‘not explicitly referred’; +: ‘briefly referred’; ++: ‘emphatically referred’.

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Data availability statement

Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.