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The purpose of this paper is to develop an indicator framework for measuring sustainable logistics innovation (SLI) in retail.

A literature review in different theory areas was conducted to generate a literature-based SLI indictor framework. The literature-based framework was then compared to five-year sustainability reports of three Swedish retailers to identify SLI indicators and how to measure them. This comparison led to a developed framework.

The developed framework combines sustainability dimensions with logistics activities. It identifies SLI indicators and how to measure them. Significant gaps between the framework and sustainability reports prompted the creation of an agenda for future research. Items that further research should consider include broadening or deepening the framework, developing specifically social SLI indicators for all logistics activities and developing measurement scales for the SLI indicators.

The study presents an SLI indicator framework as an initial contribution towards knowledge creation, and following the agenda for further research could generate even more implications for research.

Managers need inspiration concerning which indicators to use to measure SLI and how.

The study addresses both environmental and social sustainability, as well as suggests SLI indicators.

No identified study has merged sustainable logistics innovation and performance measurement in retail.

The purpose of this paper is to observe how to invest in upper-middle income countries via an innovation perspective following global innovation index (GII) by multicriteria decision aid (MCDA) approach, once MCDA was designed to support subjective decisions.

Pearson’s correlation was the milestone for understanding innovation indicators at upper-middle income countries profiles. In a MCDA first step, the analytical hierarchy process (AHP) was applied to obtain the criteria weight. In this step, the judgments or evaluations inputted in AHP were collected from a sample composed by five experts in GII. After getting the criteria weights compose to GII, Borda and Preference Ranking Organization Method for Enrichment Evaluations (PROMÉTHÉE) methods were applied to obtain an MCDA-based GII. The inputs for this second step were: the weights come from AHP output; and the countries performance came from GII data.

As a result, it was found out the upper-middle countries’ rank to invest and groups with countries acting like “hubs” or “bridges” for economic sectors in near countries; when they are grouped according to their maximum and minimum scores profiles, observing not only a particular region but also similar profiles at diverse world areas.

Pearson-AHP-PROMÉTHÉE works as a supportive decision tool for several and complex investment perspectives from criteria and alternatives analysis regarding innovation indicators for upper-middle income countries. This combination also demonstrates grouping possibilities, aligning profiles and not only ranking countries for investment and eliminating others but also grouping countries with similar profiles via innovation indicators MCDA combined application.

This paper aims to discuss the impact of institutional pressures on the selection of the performance indicators in 83 balanced scorecards (BSC) used in French real estate companies. The author studied the way in which two factors that are representative of institutional pressures in the real estate sector – namely, “ecology” and “digital innovation” – were incorporated into the BSC causal chains.

The author’s methodology is that of action research. To analyze the balance of indicators between short and long term, the author classified the companies according to their strategic acuity, i.e. their ability to balance an organizational vision (near vision) and an environmental one (distance vision) when choosing their performance indicators. This resulted in a company classification with three categories: emmetropic, hypermetropic and slightly myopic.

This research enabled to observe that the selected ecological indicators in BSCs derive mainly from coercive institutional pressure. Hence, in companies with fewer legal requirements in ecological matters, the selected ecological indicators are included in the BSC causal chain, in that they are used as a commercial argument with a view to improving financial performance. These results are similar to the reactionary and reputational perspectives of the sustainability business case. With regard to the incorporation of digital innovation indicators into BSCs, the author found that the companies that have the most digital innovation indicators are those that mobilize the most ecological indicators. Digital innovation indicators are part of the companies’ internal process perspective and are linked to organizational learning indicators. These results are similar to the responsible and collaborative perspectives of the sustainability business case. The author also found that the companies incorporate digital indicators into their BSCs by institutional mimicry insofar as the selected indicators are not always consistent with a strategic rationale but are chosen by copying what is done in other companies.

The author’s research has two main limitations related to the methodology used. On the one hand, the mobilization of part-time management students to have access to companies can influence the emergence of mimetic isomorphisms. Indeed, these students follow the same training and advise the companies that welcome them according to the training they have followed. On the other hand, the author’s research stops at the development of the BSC. The author does not study the impacts or changes that occurred after the implementation of the tool. This could be the subject of future research on the appropriation and use of the BSC by the company’s actors and their impact on the optimization of global performance measurement system.

This study may be of interest to researchers and managers who wish to reconcile sustainable development and digital innovation in global performance management. It analyzes the impact of institutional pressures on the performance measurement system. It offers insights on how to integrate ecological indicators and digital innovation indicators into the BSC causal chains. It identifies the tensions that managers may face. It reports on practices adopted in the field by managers in action.

This paper reveals the feasibility of measuring global performance integrating ecology and digital innovation. It responds to a preoccupation of recent years in academic research on how to reconcile corporate social responsibility and technological innovation. It shows that the companies that have the most digital innovation indicators are those that mobilize the most ecological indicators. However, it highlights the difficulties encountered by managers in the field when faced with institutional pressures.

The author’s reflection is in line with the literature of recent years that reconciles sustainable development and innovation. The author studied how “ecology” and “digital innovation” are incorporated into the BSC causal chains. To the best of the author’s knowledge, this is the first time this type of study has been conducted in the literature.

A growing number of African countries are starting to produce science, technology and innovation (STI) indicators. The purpose of this paper is to provide some lessons learnt in the production and use of STI indicators in Malawi and South Africa. It is compares the two countries’ efforts to conduct Research and Development (R&D) surveys and examines whether and how STI indicators are used in policymaking processes.

The study approach is qualitative. The research methodology encompasses a thorough review of both policy and academic literature as well as some interviews.

The study demonstrates that South Africa has a relatively developed institutional arrangement for undertaking R&D and innovation surveys and developing related STI indicators. There is evidence that efforts are being made to use STI indicators to inform policymaking in the country. On the other hand, Malawi conducted its first R&D survey under the African Science, Technology and Innovation Indicators Initiative (ASTII) and has not established an institutional mechanism dedicated to producing STI indicators. There is no evidence that indicators are used in, or to inform, policymaking in the country.

Because of significant differences in STI policymaking histories, capacities and cultures of the two countries, it is not really useful to compare the STI production and use. Rather it is important to draw lessons from the efforts of the two countries.

The results suggest that the production of STI indicators should be embedded in policy processes. To be useful and effective, STI indicators production needs to be explicitly linked to policy formulation, evaluation and monitoring activities without necessarily undermining the independence of producing STI indicators.

Creating stand-alone programmes or agencies for R&D and innovation surveys without clear articulation with policymaking needs erodes opportunities of having evidence-based STI policy regimes.

Although in 2005 only South Africa and Tunisia had national programmes dedicated to the generation of R&D statistics, by the end of 2010 at least 19 African countries had experimented with conducting R&D surveys under the auspices of the ASTII of the New Partnership for Africa’s Development. These countries accumulated different experiences and consequently build different kinds of institutional capacities. Through the Malawi and South Africa case studies, some important lessons for STI indicators production and use and STI policymaking can be drawn for developing countries in general and African countries in particular.

The implementation of the innovation-driven development strategy is of practical significance for improving the quality and efficiency of economic growth and accelerating the transformation of economic development mode. The purpose of this paper is to study the impact of innovation-driven strategies on marine industry agglomeration and industrial transformation.

In traditional grey correlation analysis, when the positive and negative areas cancel each other out during the integration process, the calculation result of the correlation degree is often inconsistent with the qualitative analysis. For this reason, from the perspective of curve similarity, this paper constructs two response curves through the relative change area of the two curves and the relative area change ratio of similar degree, thus constructing an improved grey relational model.

The authors find that the innovation investment has a better correlation with marine industrial agglomeration. It also found that Guangdong Province has the highest degree of correlation between innovation indicators and marine industrial agglomeration. Much beyond the authors’ expectation, in the areas where marine industrial agglomeration is high, the synergistic effect is not obvious by using the location entropy method.

The improved grey correlation analysis method can effectively overcome the phenomenon that the positive and negative areas cancel each other in the integration process of the original algorithm, and it can also effectively measure the negative correlation between variables. This paper explores the impact of innovation drive on the agglomeration of marine industries, which is of great significance to the sustainable development of marine economy.

The measure of companies' Innovation Performance is fundamental for enhancing the value and decision-making processes of firms. The purpose of this paper is to present a new measure of Innovation Performance, called Innovation Patent Index (IPI), which makes it possible to quantitatively summarize different aspects of firms' innovation.

In order to define the IPI, a secondary source, i.e. patent data, has been used. The five dimensions of IPI, i.e. efficiency, time, diversification, quality and internationalization have been defined both analyzing the literature and applying three different machine learning algorithms (regularized least squares, deep neural networks and decision trees), considering patent forward citations as a proxy of the innovation performance.

Results show that the IPI index is a very useful tool, simple to use and very promptly. In fact, it is possible to get important results without making time consuming analysis with primary sources. It is a tool that can be used by managers, businessmen, policymakers, organizations, patent experts and financiers to evaluate and plan future activities, to enhance the innovation capability, to find financing and to support and improve innovation.

Patent data are not widely used in all the sectors. Moreover, the pure number of forward citations is not the only forward looking indicator suggested by the literature.

The demand for a useable Innovation Performance tool, as well as the lack of tools able to grasp different aspects of the innovation, highlight the need to develop new instruments. In fact, although previous studies provide several measures of Innovation Performance, these are often difficult for managers to use, do not appreciate different aspects of the innovation and are not forward looking.

The purpose of this paper is to evaluate the international position of Estonia among the member states of the EU and countries closely associated with the EU, from the perspective of the effect of research and development (R & D) policy on innovation activities in the business sector.

Based on existing scientific research literature on the relationships between R & D policy and business sector R & D activities and innovation performance, a set of indicators describing R & D policy measures was created for the business sector. Using principal component analysis (PCA) method, independent robust dimensions of R & D policy were brought out. After eliminating the problem of multicollinearity in R & D policy indicators, robust multiple regression models were conducted to present a comprehensive empirical description of the shaping of business sector R & D and innovation activities in the sample of investigated countries.

Based on the literature, the influences of R & D policy measures on business sector R & D activities and innovation performance were systemised; public R & D policy dimensions were empirically defined; the intensity of R & D policy influence on business sector R & D activities was estimated; the differences between real and prognostic values of business sector performance indicators in Estonia were calculated in order to characterise the efficiency of Estonian R & D policy and the influence of the socioeconomic environment.

The lack of comparable data describing R & D policy and R & D activities and innovation performance in the business sector limits the comprehensiveness of the analysis (i.e. the number of analysed indicators).

The assessment and comparative analysis of the influence of R & D policy components on business sector R & D activities and innovation performance in different countries makes it possible to identify directions for increasing the efficiency of R & D policy under the specific influence of the socioeconomic environment, especially in new member states of the EU.

Using the PCA method significantly increased the robustness of the macro-quantitative description of R & D policy dimensions. By combining the set of new synthetic R & D policy indicators created by the PCA with the multiple regression analysis method, a significant increase in the robustness of model coefficients (i.e. the assessments of influence intensity) was achieved. These robust models create the basis for reliable empirical assessment of the influence of R & D policy and a comparative analysis of the results.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).

This research paper aims to contribute to the field of innovation performance benchmarking by identifying appropriate benchmarking groups and exploring learning opportunities and integration directions.

The study employs a multi-dimensional innovation-driven clustering methodology to analyze data from the 2019 edition of the Global Innovation Index (GII). Hierarchical and K-means Cluster Analysis techniques are applied using various sets of distance matrices to uncover and analyze distinct innovation patterns.

This study classifies 129 countries into four clusters: Specials, Advanced, Intermediates and Primitives. Each cluster exhibits strengths and weaknesses in terms of innovation performance. Specials excel in the areas of institutions and knowledge commercialization, while the Advanced cluster demonstrates strengths in education and ICT-related services but shows weakness in patent commercialization. Intermediates show strengths in venture-capital and labour productivity but display weaknesses in R&D expenditure and the higher education quality. Primitives exhibit strength in creative activities but suffer from weaknesses in digital skills, education and training. Additionally, the study has identified 35 indicators that have negligible variance contributions across countries.

The study contributes to finding the relevant countries’ grouping for the enhancement of communication, integration and learning. To this end, this study highlights the innovation structural differences among countries and provides tailored innovation policies.

Innovation project development is becoming more important in boosting competitiveness of universities and enterprises. It will not be possible to ensure rapid economic growth of enterprises without competitive innovations and without their introduction into education and business practice. The object of the research paper is innovations in teaching entrepreneurship. The subject of the research paper is analysis of the effective entrepreneurship education at the universities. The objective of the research paper is to study the integration process of technological business environment (TBE), intellectual capital (IC) formation, innovation project (IP) development at the universities and enterprises.

The tasks advanced in order to reach the objective: to identify the concept of IC, IP, the methodology of IP development at the universities, their main actions and methods; to carry out analysis of the TBE in Latvia, indicators characterizing it environment, the factors of TBE influencing IC, IP development at the universities and enterprises; to estimate the IP development as the teaching method at the universities and business practice in Latvia. The research period is from the year 2007 till the year 2020. This is the first research on the analysis of indicators of TBE influencing IC formation, IP development at the universities; the efficiency of involvement of academic staff in the formation of IC and IP development into entrepreneurship education in Latvia; definition of the IP development as the teaching method and presentation of its theoretical and practical interpretation.