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The purpose of this study is to explore the interplay among self-organization, networks and sustainable innovations within microfinance institutions (MFIs) and to examine the extent to which organizational resilience plays a significant role in shaping these dynamics as a mediator.

This paper adopted a cross-sectional research design combined with analytical and descriptive approach to collect the data. Smart partial least squares structural equation modeling (PLS-SEM) was used to construct the measurement model and structural equation model to test the mediating effect under this study.

The results revealed that organizational resilience is a significant mediator in the relationship between self-organization, networks and sustainable innovations among microfinance institutions in Uganda.

The data for this study were collected only from microfinance institutions in Uganda. Future studies may collect data from other formal financial institutions like commercial banks and credit institutions to test the mediating effect of organizational resilience. More still, the study adopted only a single approach of using a questionnaire. However, future research through interviews may be desirable. Likewise this study was cross-sectional in nature. Therefore, a longitudinal study may be useful in future while investigating the mediating role of organizational resilience traversing over a long time frame.

A possible implication is that microfinance institutions which desire to have sustainable innovative solutions for their business operations in disruptive circumstances may need to scrutinize their capacity to be resilient and self-organize.

Microfinance institutions play a great role to the underserved clients. Thus, for each to re-organize to be able to provide services that meet users’ needs, without physical products so as to ensure long-term financial and social welfare combined with the ability to bounce back and adapt in times of economic downturn to avoid mission adrift.

While most studies have been carried out on organizational resilience, this paper takes center stage and is the first to test the mediating role of organizational resilience in the relationship between self-organization, networks and sustainable innovations, especially in microfinance institutions in Uganda. This paper generates strong evidence and contributes to the powerful influence of organizational resilience in enhancing the level of sustainable innovations based on self-organization and networks.

In this study, the authors examine artificial knowledge as a fundamental stream of knowledge management for sustainable and resilient business models in supply chain management (SCM). The study aims to provide a comprehensive overview of artificial knowledge and digitalization as key enablers of the improvement of SCM accountability and sustainable performance towards the UN 2030 Agenda.

Using the SCOPUS database and Google Scholar, the authors analyzed 135 English-language publications from 1990 to 2022 to chart the pattern of knowledge production and dissemination in the literature. The data were collected, reviewed and peer-reviewed before conducting bibliometric analysis and a systematic literature review to support future research agenda.

The results highlight that artificial knowledge and digitalization are linked to the UN 2030 Agenda. The analysis further identifies the main issues in achieving sustainable and resilient SCM business models. Based on the results, the authors develop a conceptual framework for artificial knowledge and digitalization in SCM to increase accountability and sustainable performance, especially in times of sudden crises when business resilience is imperative.

The study results add to the extant literature by examining artificial knowledge and digitalization from the resilience theory perspective. The authors suggest that different strategic perspectives significantly promote resilience for SCM digitization and sustainable development. Notably, fostering diverse peer exchange relationships can help stimulate peer knowledge and act as a palliative mechanism that builds digital knowledge to strengthen and drive future possibilities.

This research offers valuable guidance to supply chain practitioners, managers and policymakers in re-thinking, re-formulating and re-shaping organizational processes to meet the UN 2030 Agenda, mainly by introducing artificial knowledge in digital transformation training and education programs. In doing so, firms should focus not simply on digital transformation but also on cultural transformation to enhance SCM accountability and sustainable performance in resilient business models.

This study is, to the authors' best knowledge, among the first to conceptualize artificial knowledge and digitalization issues in SCM. It further integrates resilience theory with institutional theory, legitimacy theory and stakeholder theory as the theoretical foundations of artificial knowledge in SCM, based on firms' responsibility to fulfill the sustainable development goals under the UN's 2030 Agenda.

Urban metropolitan consumers react to the different qualitative categorizations of the product thus creating homogeneous market segments. The aim of this paper is to identify specific market segments which allow for the definition of homogeneous olive oil consumer targets.

This study was based on the stated preferences of consumers and emphasizes the role that different quality scales of olive oil have in the eye of the consumer. The data, collected through a questionnaire, were analysed by means of inferential and multivariate statistics techniques, that is, the study specifically entailed a factorial and cluster analysis.

This paper explores olive oil market segments broken down by the different quality levels of existing products, thus trying to identify main consumer preferences. Our outcomes suggest the existence of three main quality classes of olive oil consumer: basic, popular and premium.

Even though we gathered data and information from a broad sample, the study does not fully reflect the average Italian population since we based our study on a convenience sample of northern Italian consumers. A more extended sample is needed to test our hypothesis in other regional areas.

The outcomes derived from this study provide useful insights both for marketers and olive oil producers by allowing more efficient strategic decisions in terms of product segmentation.

This study, aimed at matching olive oil market segments and consumer preferences, shows the existence of three well-defined quality classes of olive oil consumer: basic, popular and premium. In addition, this study ascertains for the first time how the attitude towards local products is positively influenced by family origin as a result of an inter-generational attitude.

The current paper aims to discuss the implementation of Green Lean Six Sigma (GLSS) in the food industry to improve sustainable practices. The focus is more specifically on dairy processors to ascertain the current state of the literature and aid future research direction.

Utilising a systematic literature review (SLR), the paper addresses various terms and different written forms in the literature. The study characterises the current deployment of GLSS in the food industry and explains the reported benefits of this approach.

GLSS, a concept that has yet to be fully explored in the food industry, as in other sectors, holds significant potential to enhance the food industry’s sustainability practices. The dairy sector, a subsector of the food industry known for its high greenhouse gas emissions, is a prime candidate for the application of GLSS. In instances where it has been applied, GLSS has demonstrated its effectiveness in improving sustainability, reducing waste, lowering greenhouse gas emissions and minimising water usage. However, the specific tools used and the model for GLSS implementation are areas that require further study, as they have the potential to revolutionise food industry operations and reduce their environmental impacts.

Benchmarking of this research by the food industry sector and by academics can aid understanding of the practical application of GLSS tools and aid implementation of these practices to evolve the dairy processing sector in the next decade as sustainability champions in the sector.

This study extensively analyses GLSS in the food industry, with a particular focus on dairy processors.

The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.

Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.

Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.

The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.

This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.

This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.

Gastronomy can be a key destination choice factor. As tourists, people will be able to learn more about the culture of the place through its culinary assets. This paper aims to analyse the interest and the gastronomic motivations of tourists to the city of Granada (Spain), where two important UNESCO World Heritage Sites (WHS) are included.

To achieve the aim of this study, fieldwork was carried out on a representative sample of tourists in Granada (Spain). Specifically, a total of 1,612 valid surveys were filled out in culinary establishments and historical sites. In these surveys, the opinion of tourists regarding gastronomy and their motivations when travelling was assessed.

The results of this research allow to make a segmentation of tourists into three groups according to their position and their interest in gastronomy based on their destination choice, distinguishing among survivors, enjoyers and experiencers’ tourists. Additionally, it is confirmed that gastronomy is shaped as a motivation that influences the level of tourist satisfaction, performing as a differentiating element that can help increase the competitiveness of the destination.

This research contributes to the scarce academic literature on tourism experiences in a city with WHS recognitions. This study confirms the existence of a relationship between gastronomic motivations and the level of satisfaction achieved by tourists who visit the city of Granada, where no similar studies were found. In addition, this work confirms the connection between gastronomy and culture.

The pervasive impact of the COVID-19 virus on the food services sector in India has created conditions for fundamentally altering the structure of the industry. This paper offers a nuanced evaluation of the transfiguration of the market, explaining descriptive views supported by numerous secondary data sources.

This is a self-driven study grounded in secondary data. Qualitative and quantitative assessments are assimilated from credible market research reports of multiple agencies in the Indian context, as well as news developments during the pandemic period.

Digitally pivoted platforms such as cloud kitchens and delivery aggregators will eclipse all other formats due to the potential long-term prevalence of the COVID-19 virus. These formats would rise to a dominant position in the Indian food services sector in the coming decade.

This study is entirely driven by secondary data due to the inherent difficulties of collecting sizeable and good quality primary data as a result of the lengthy and stringent lockdowns imposed across India. Future studies should consider collecting consumer responses to get a better picture of changing dining habits in the post-pandemic scenario.

The dynamic and evolving food services in India, catalyzed by the Internet and digital technologies will help academicians study the long-term implications of this change, and how it would impact society at large. The paper provides a rich body of contemporary data and analysis in the food services sphere.

The COVID-19 pandemic and its long-term persistence would dramatically alter food service consumption across India. This will not only change how the industry is structured, but will reshape how food is consumed into the future.

The study is a holistic examination of the relationship between the coronavirus pandemic and the food services industry in India. The macro perspectives aided by news coverage and industry research would help generate potential research questions on its own merits.

This case study aims to analyse the different factors that cause a decline in an organisation's performance. It projects data for the prospective case readers to explore the possible approaches for the Chairman-cum-Managing Director (CMD) of Mahanagar Telephone Nigam Limited (MTNL) and Bharat Sanchar Nigam Limited (BSNL) to turnaround both the organisations. Furthermore, the case compels the readers to study the Indian Telecom industry to analyse the competitive behaviour and the consequent actions necessary to survive and thrive amongst their peers. From the theoretical perspective, the case emphasises the recent change observed in the Telecom industry regarding the transition from value-chain to value-network.

The authors collected the case facts and data for the case study from secondary sources like the latest news articles, the CRISIL database, company annual statements, company press releases and government regulatory body web portals.

The case study has identified the issues pertinent in the public sector companies in India, especially in the telecom sector, concerning leadership, pending government financial commitments and a slow-moving attitude towards taking action.

The case study highlights the management problems faced by the CMD of the two public sector telecom companies i.e. BSNL and MTNL.

A flexible model which is based on a Triangular intuitionistic flexibility ranking and aggregating (TIFRA) operator is proposed for failure detection and reliability management in a Wind Turbine system. The model which is employed when there are limited research data and valid source of information, uses expert-based knowledge/opinion for failure detection and reliability management. The results from the study concludes that, the most important area affected by failure with respect to the failure criteria used, includes; oil level sensor tilt sensors for tower installation and accelerometers for tower sway (A₂), Pressure sensor for blade monitoring (A₃), and the Pitch actuator (A₄). The main advantage of the proposed method is that it provides advanced information about faults that identifies the intensity of the system behavior also; the method provides a more complete view of the reliability management and root cause of failure in the Wind Turbine (WT) system using the flexibility parameter in the model.

The purpose of the present study is to investigate travel agencies' social media usage and its perceived effectiveness by small- and micro-Italian travel agencies; the pre-pandemic period is compared to the forecasts for the post-Covid-19 period and different characteristics of firms and entrepreneurs are considered. Furthermore, the study analyses the expected benefits in terms of marketing objectives, such as improving brand image and/or personalizing the offer.

The research was developed through a questionnaire administered electronically to travel agents (282 respondents). The resulting data was analyzed by applying the McNemar test, a pairwise t-test and the multivariate analysis of variance.

The results show that social media are strategically significant for travel agents, even though their adoption is influenced by different agency aims; the perceived effectiveness results are diversified according to varying agency typologies.

The two main limitations of the study are its focus on the Italian context only and the missing consideration of the consumer's point of view. The latter prevents an exhaustive assessment of future trends regarding the use of social media in the client–agency relationship.

The study, which focuses on a little debated topic concerning the relationship between social media and SMEs, organically explores various dimensions related to the adoption of social media by small agencies, also considering the impact of the Covid-19 on the perception of travel agents. As a further element of originality, the research takes into consideration the main social platforms separately rather than the set of tools as a whole.