Innovation Performance Measurement Research Articles

Lean vs agile project management in construction: impacts on project performance outcomes

PurposeThe present research aims to investigate how lean project management (LPM) and agile project management (APM) affect project performance outcomes in the construction sector in Jordan. This study focuses on six key project performance outcomes, namely cost, time, quality, client satisfaction, innovation and responsiveness.Design/methodology/approachThe present study employed a quantitative approach to achieve the research objectives. Accordingly, a multi-item survey questionnaire was prepared to gather data from 392 project managers from construction companies in Jordan. The study’s model showed acceptable levels regarding reliability, validity, fit indices and discriminant validity. In order to test the hypotheses of this study, path analysis was employed using Amos 24.0 software.FindingsLPM demonstrated a remarkably high positive impact on cost performance. It also positively affected quality performance and client satisfaction. However, LPM insignificantly affected time, innovation and responsiveness performance measures. On the other hand, APM showed a notably high positive impact on innovation and responsiveness. The findings also revealed that APM positively impacted quality performance and client satisfaction. In addition, APM negatively impacted cost performance and insignificantly impacted time performance.Originality/valueThis study is one of the first comprehensive studies to empirically examine the impact of both LPM and APM on various project performance outcomes in the construction industry in the context of a developing country. It reveals some similarities and differences between LPM and APM with regard to their impacts on project management outcomes. The findings are expected to guide managers in selecting the appropriate project management approach based on the desired performance outcomes. Accordingly, it offers important implications for project managers in construction companies.

Dynamics of digital change – measuring the digital transformation and its impacts on the innovation activities of SMEs

PurposeDigital transformation has gained particular interest among academics and policymakers in recent years. However, the empirical quantification of digital transformation stages and their impact on innovation in small and medium-sized enterprises (SMEs) remains understudied. Therefore, this study aims to investigate the impact of digital transformation stages on a differentiated measurement of innovation performance in SMEs.Design/methodology/approachThe authors propose a simplified one-dimensional digital maturity path to estimate the stages of digital transformation in SMEs. The authors validate their approach with a cluster analysis and perform an ordered logistic regression to estimate the impact of digital transformation stages on SMEs' innovation performance.FindingsThe authors' results show that digital transformation in general has a positive impact on SMEs' innovation performance. More precisely, the authors find that the early stage of digital transformation has a detrimental effect on innovation performance, while significant and positive effects can be expected from the experimental stage onward. Furthermore, the advanced stage of digital transformation significantly increases the probability of producing radical innovations.Originality/valueThis study contributes to the ongoing discussion about the relationship between digital transformation and innovation in SMEs by presenting an approach to quantify digital transformation stages in SMEs. Additionally, this study provides new insights into the specific dynamics of the relationship between different stages of digital transformation and their impact on a differentiated measurement of innovation performance, including technological, non-technological and radical innovation.

A Machine Learning-Based Approach to Identifying Key Innovation Determinants for Industrial Firms: The Case of the Pharmaceutical Industry in China

With abundant resources consumed by innovation practices, it is of strategic importance for industrial firms to identify key determinants of innovation performance from both internal and external environments for better and effective innovation management. To this end, this article develops a new machine learning-based approach to examine a variety of factors influencing innovation performance. In particular, a two-process modeling approach is developed to build machine learning models efficiently for identifying key internal and external innovation factors. With extensive experiments using data collected from China's pharmaceutical industry, the approach identifies a set of key internal and external innovation factors and their best configurations in terms of two commonly used innovation performance measures. The findings enable pharmaceutical firms and local governments in China to manage innovation efforts and formulate management strategies for promoting industrial innovation. The article contributes to innovation management research by providing an objective and data-oriented approach for comprehensively exploring internal and external innovation factors and establishing their relationships with expected innovation performance. Although the approach is exemplified by China's pharmaceutical industry and the results cannot be generalized, it has general applicability to other industries or countries.

Identify more inefficiency sources to firm's innovation performance: low-value patent or R&D expenditure congestion?

ABSTRACTInnovation performance is critical to strengthening the market competitiveness of firms, but it would always be impaired by low-value patents and innovation resource waste. It is ideal for firms to identify the inefficiency sources in innovation performance and launch target improvements. Therefore, this study proposes a novel method framework of data envelopment analysis (DEA) to measure innovation performance and examine the inefficiencies caused by low-value patents and R&D expenditure waste. Under the proposed method, patent value is measured by the shadow price, and R&D expenditure congestion is identified as a form of waste. To prove its effectiveness, the method is applied to a case of 375 Chinese high-tech firms. Empirical findings are as follows. The presence of low-value patents and R&D expenditure waste are verified. Innovation performance is negatively affected by R&D expenditure waste but positively influenced by patent value. Moreover, higher patent value and greater R&D expenditure congestion ratio are found in firms with high-tech park locations, large sizes and international ownership, showing a positive correlation between patent value and R&D expenditure waste. The findings identify detailed inefficiency sources of firms’ innovations and provide solid managerial suggestions.

Innovation Performance Measurement in Entrepreneurial Business: A Comparative Study between Start-ups and More Established Enterprises

Innovation performance measurement is an important aspect of understanding and improving entrepreneurial success, which has implications for economic development, organizational growth, and community welfare. This study uses comprehensive bibliometric analysis to systematically review and analyze the literature on innovation performance measurement in entrepreneurial business. The research covers startups and established companies, aiming to uncover key themes, influential works, and an ever-evolving research landscape in this dynamic field. His methodological approach integrates bibliometric analysis and visualization using VOSviewer, which provides a holistic view of the intellectual structure in the domain. Key findings include the identification of thematic groups, influential authors, and important works, which provide valuable insights for academics, practitioners, and policymakers involved in fostering innovation and entrepreneurship.

The approach to and challenges in measuring innovation in China

In China and elsewhere, innovation features strongly in government policy as a key driver of economic development. Being able to measure innovation performance is therefore important. This paper analyses China’s approach to measuring the country’s innovation performance. In doing so and using documentary analysis, it evaluates the conceptualisation and data collection that underpin and support that measurement. The findings show that China focuses on a science and technology approach to measuring innovation. The weaknesses of this approach are identified: first, the conceptual scope is too narrow due to its exclusion of non-technological innovation; second, relatedly, data gathering is limited quantitatively and qualitatively in its coverage of types of innovation; and, third, the sample population is biased, acting to excluding a significant number of firms and employees. These weaknesses undermine understanding of innovation performance in China. With this analysis, this paper provides the first evaluation of China’s innovation conceptualization and measurement and, based on the findings, provides suggestions to address these weaknesses and improve the measurement of innovation performance and which have applicability beyond China. For China and other countries such as those which are members of the OECD and EU, the evidence provided in this paper suggest that there is a pressing need to adopt this broader policy approach and support it through the development of appropriate measures and data collection.

Exploring the use of innovation measurement in retail organisations: a multiple case study

ABSTRACT Innovation and its management in retail organisations is an emerging field, yet the measurement of innovation in this context remains challenging and under-researched. The study investigates innovation in large Swedish retail companies, focusing on monitoring and measurement of innovation performance. Through a qualitative, multiple case study, our findings reveal that retailers are aiming to become more active innovators. They are exerting a greater control over the innovation process, implementing a range of financial and non-financial indicators that encompass inputs, outputs, and the process itself. Innovation projects serve as vehicles for experimentation and learning about how to improve the structure of innovation efforts. However, challenges still arise when strategic objectives are not aligned with performance measurements across the organisation. Nonetheless, existing performance measurement practices can support innovation capability development in retail, especially in relation to culture and competence development and utilising external knowledge for open innovation. The paper advances theory by offering insights into how retailers gain more control of innovation through measurement, contributing to the growing landscape of strategic innovation management in retail. We propose a model, informed by theoretically built framework and empirical data, to guide retail organisations in defining new measurements that promote a holistic perspective to building innovation capability.

Implementing and assessing a performance framework for the innovation measurement in a European manufacturer

PurposePerformance framework (PF) is a well-established practice to measure innovation performance and identify improvement opportunities. However, whether PFs academic research are applicable to companies remains unclear, as well as their support in the definition of improvement actions. This study aims to present the implementation and assessment of a new and updated PF proposed in previous research in a real industrial context.Design/methodology/approachThe PF was implemented through an in-depth case study carried out in a European machinery manufacturer and further assessed by practitioners.FindingsThe results indicate that the PF enabled the creation of a multidimensional view of the innovation performance and the definition of improvement projects in the company. Additionally, the findings also reveal an overall positive assessment of the PF by senior managers who work with the innovation process.Research limitations/implicationsAs a case study, this research is inherently limited in the extent to which results can be generalised. Thus, the analyses are reductive and rationalising. Future research is needed to assess the replicability of the PF.Practical implicationsThe study's practical contribution is based on the combination of insights and steps that provide a straightforward and actionable approach for the company to improve performance.Originality/valueThis study aims to advance the importance of implementing the new and updated PF after its proposition, which is often overlooked in preceding research. Furthermore, the assessment of the PF also enables to infer its value to the company's employees.

신용등급과 기업의 혁신활동

This study examines the impact of credit ratings on corporate innovation activities. A sample of domestic securities-listed companies is selected, and changes in innovation activities are investigated when firms exhibit high sensitivity to credit ratings. Credit rating data from December settlement companies, spanning the period from 2002 to 2019, excluding the financial industry, is employed. A total of 2,179 company-year observations are used, which include corporate patent data as a proxy for measuring innovation performance, to examine the relationship between credit ratings and innovation activities. Furthermore, the study analyzes how these relationships vary across high-tech and non-high-tech industries, as well as investment ratings and speculative ratings.
 The empirical analysis reveals a significant positive relationship between the sensitivity of firms to credit ratings and their innovation activities. Specifically, firms that are more sensitive to credit rating downgrades show an increase in innovation activities, while no significant results are found for credit rating upgrades. This suggests that firms with a higher likelihood of credit rating downgrades are more likely to actively pursue innovation activities to maintain their current credit rating. Moreover, this asymmetric relationship between credit ratings and innovation is more pronounced in high-tech industries compared to non-high-tech industries, and in investment-rated firms compared to speculative-rated firms. Based on these empirical findings, this study provides important implications for stakeholders and financial market participants regarding the relationship between credit ratings and innovation.

Lean performance measurement system for an Indian automotive supply chain

PurposeThis paper aims to present a simple and innovative fuzzy methodology-based lean performance measurement system (L-PMS) for an Indian automotive supply chain. The paper also enlightens the influence of coronavirus disease 2019 (COVID-19) on supply chains and the practical implications of the unprecedented disruptions on the performance measurement systems.Design/methodology/approachThe L-PMS is divided into three phases. In the first phase, the key performance indicator (KPI) list, as deemed fit by the organization, is prepared using literature and suggestions from the case organization. The list contains 61 KPIs measuring 24 performance dimensions in seven functional areas of the supply chain. In the second phase, the KPI performance data (actual, best and worst) are collected using the enterprise resource planning (ERP) system. In the last phase, the leanness score of the case organization is calculated at four levels – KPI, dimension, functional area and overall organization.FindingsThe overall leanness score of the case organization is 60%. The case organization uses KPIs from all seven functional areas, but it needs to improve the number of KPIs in administration and supplier management functional areas. The case organization uses only quantitative KPIs. However, the performance dimensions at the middle level are adequate. The leanness level of the case organization in different areas is highly variable (ranges from 45% to 91%).Research limitations/implicationsThe major limitation of the study is that the case study is done at a single organization.Practical implicationsThe managers at the different levels of the hierarchy can use the lean performance measurement score to leverage the better performing areas/dimensions/KPIs and improve poor performing areas/dimensions/KPIs. The lean performance measurement at functional area level can help leadership to give responsibility to different people for the improvement of leanness with respect to different dimensions/functional areas. The disruptive impact of COVID-19 should clearly be understood by the managers to make appropriate decisions based on the severity as measured at different levels.Originality/valueAccording to the authors' best knowledge, this is the first lean performance measurement application at the four hierarchical levels (KPI, performance dimension, functional area and overall organization).

Framework for Measuring Innovation Performance in Higher Education Institutions

Framework for Measuring Innovation Performance in Higher Education Institutions

Customers’ perception of telecommunication businesses: Non-financial performance measures in organizational success

Performance measures drive an organization’s success. The measures improve strategic communication with stakeholders. Based on customer survey data, this study aimed to examine the association between the use of non-financial performance measures (NPMs) and organizational success (OS) in the Nepalese telecommunication business. The study used a descriptive strategy and a structured survey questionnaire to collect data from the targeted respondents. It gathered 385 responses based on the convenience sampling technique. The questionnaire contained two items relating to the respondent’s demographics, 19 items relating to NPMs, and seven items on organizational success. The NPMs were grouped into three constructs by employing confirmatory factor analysis. The analysis indicated that the technological and innovation performance measures had the most significant contribution, followed by the social and environmental performance measures and the customers’ performance measures to the organizational success. The study found that NPMs explained 62.9% of telecommunication business’s success, indicating more reliance on NPMs increases performance and success. Such findings would provide crucial information for comprehending the NPMs and validate Adhikari and Chalise’s (2021) conclusions that the performance evaluation system for the Nepalese telecommunications business has changed to reflect strategic goals by adding NPMs.

Green innovation performance measurement and international comparison of ceramic industry clusters

Green innovation performance measurement and international comparison of ceramic industry clusters

Novel Comprehensive MEREC Weighting-Based Score Aggregation Model for Measuring Innovation Performance: The Case of G7 Countries

Innovation can be the greatest hope of overcoming economic challenges. This paper aims to evaluate countries concerning their innovation performances. We introduce an innovation performance evaluation methodology by considering objective factors and applying seven reliable MCDM methods: MEREC, CODAS, MABAC, MARCOS, CoCoSo, WASPAS, and MAIRCA. MEREC calculates the relative weights of indicators considered, while the other techniques decide the ranking order of G7 countries. The Borda rule is then employed to gain an aggregated ranking order. “Business sophistication” is the most critical indicator, whereas the US has the best position regarding the overall ranking. Sensitivity control is as well conducted.

Innovation Performance Measure Tension and Absorptive Capacity

In pursuit of innovation, most firms rely on a diverse set of performance measures. While this helps them manage their various innovation efforts, the inherent tension between very distinct measures may also come at a cost. In this study, we argue that a strong tension between radical and incremental innovation performance measures undermines employees’ ability to effectively search and integrate knowledge from outside the organization’s boundaries, thus reducing a firm’s absorptive capacity. Firms may, however, overcome this problem through cultural controls. More specifically, we argue that encouraging paradoxical thinking among employees helps them cope with the contradictory nature of performance measure tension, thereby improving both their search and integration strategies for new knowledge. We test our hypotheses using survey data from 131 companies in innovation-dependent industries and find support for our predictions. A supplementary analysis provides evidence that the mechanisms we present also have significant performance implications for firms.

Epistemic Plasticity and Innovation in Data-driven Organizational Cultures

A long tradition in innovation research asserts that data-driven organizations excel at incremental innovation, but allocate resources away from less-measurable breakthrough innovations. Questioning this premise, I distinguish the magnitude of an organization’s use of quantitative analysis from the epistemic plasticity of its organizational culture (the extent to which its members use different kinds of analyses). I argue that organizations using more quantitative analysis will actually produce more breakthrough innovations—provided that their cultures are plastic enough to use qualitative analysis liberally as well. To test my theory, I measure innovation performance using product-level sales and attribute data for over 3,500 consumer product launches from 61 organizations between 2010 and 2016; I measure use of qualitative and quantitative analyses using natural language processing on employee résumés. I find that increased reliance on quantitative analysis decreases innovation performance when qualitative analysis is low, and, conversely, increases when qualitative analysis is high. Additional analyses show that this relationship is particularly strong for novel products, and in markets characterized by high uncertainty. I also explore antecedents: management fads, not organizational learning, appear to account for excessively data-driven cultures. The paper contributes to organizational theories of innovation, and to research linking organizational culture to strategic performance.

Open Innovation Performance in SMEs: Strategic Insights from Patent Analytics

Prior research has identified a positive relationship between open innovation collaboration and innovation performance. This paper asks whether this positive relationship reported in the literature is partially driven by measurement error, e.g., misclassifications of firms’ intra-group transfers of knowledge as interactions external to the firms. Using a unique, self-compiled secondary dataset of 21,898 patent families from 44 German small- and medium-sized enterprises with 9,902 entities, we show that open innovation collaboration’s impact on innovation performance becomes insignificant when measurement distinguishes between patents from collaborations by firms within and firms beyond the same corporate trees. Boundary conditions and robustness checks yield stable results when tested against 12 patent quality-based measures of innovation performance. Our contributions motivate to revisit the assessment of open innovation performance to prevent biased results and suboptimal decision-making in implementing innovation and subsequent commercialization strategies across firms’ boundaries. We further show that complementing open innovation theory with patent quality measures enriches analytical options and allows additional insights. This adds to the broader understanding of open innovation theory, in particular open innovation outcomes.

Relationship between ecosystem innovation and performance measurement models

PurposeThis study examines the relationship between the innovation ecosystem and performance measurement models. Although the innovation ecosystem and measurement models are widely recognized, the existing literature lacks a comprehensive understanding of the relationship between the proposed themes. Furthermore, it does not reveal how studies can be grouped to propose a thematic typology of the relationship.Design/methodology/approachThe authors present a systematic literature review conducted in the Web of Science and Scopus databases, from a textual corpus that aided the proposition of the typology that aims to provide answers regarding the addressed themes.FindingsThe results of this review are based on a total of sixty peer-reviewed articles from the innovation ecosystem literature and performance measurement models between 1995 and 2020. The results make several contributions to the literature. First, by integrating evidence from empirical studies, the authors identified a typology formed by three classes: (1) ecosystem agents (2) analytical focus and (3) structured measurement tools. Second, the authors verified the relationship between the themes and discovered the existence of gaps to be filled, with the proposition of three drivers. Third, the authors presented a comprehensive mapping of field studies with a descriptive analysis of the textual corpus.Originality/valueThe results of the research provide important implications for researchers, managers and policy makers. Furthermore, the authors suggest directions for future research, including the need to examine the performance of the entire innovation ecosystem, integrating the different agents that exist for performance measurement.

EVALUASI KEBIJAKAN TENTANG MANAJEMEN INOVASI PERGURUAN TINGGI (MIPT) DI PERGURUAN TINGGI NEGERI

Policy Evaluation of the Ministry of Research, Technology and Higher Education Regulation No. 24 of 2019 aims to encourage The University (PT) to manage innovations that impact people's lives. The management of innovation in State Universities (PTN) is not optimal as expected. For this reason, the implementation of Higher Education Innovation Management (MIPT) is expected to play an optimal role in facilitating and realizing the improvement, development, and utilization of research results in PTN. Steps and strategies are taken by the Ministry of Research and Technology (Kemristek)/National Research and Innovation Agency (BRIN) to realize research innovations in PT, specifically by encouraging the implementation of Innovation Management in their respective PT. In addition, they are providing technical guidance in measuring innovation performance to provide the expected results, namely strengthening innovation at PT. The implementation of MIPT in PTN has been effectively implemented and has become the primary goal of PTN, but there are still obstacles in its implementation. Several factors of emphasis in increasing the productivity of innovation performance are related to the number of researches, inventions, innovation products, strengthening innovation management institutional policies, and organizational arrangements that require the formation of innovation management institutions. The challenges of PTN in MIPT are related to the stages of commercializing innovation products to the industrial world, managing Intellectual Property Rights and Patents. Some recommendations that need to be considered are the need for continuity of socialization, the availability of technical modules that provide detailed explanations of what PTN must do in managing innovation and clarity of authority over the Regulation No. 24 of 2019 concerning MIPT. Keywords: Evaluation, Higher Education Innovation Management, Policy

Measuring the financial impact of equipment performance improvement: ISB and IEB metrics

PurposeEquipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.Design/methodology/approachThe research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.FindingsThe findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.Practical implicationsManufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.Originality/valueThe study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.