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This study aims to investigate organizational learning, represented by the absorptive capacity, as a condition for the firm to learn about marketing data and make more informed decisions. The authors also aimed to understand how the behavior of micro, small and medium enterprises (MSME) businesses differ in this scenario through a multilevel perspective.

Placing absorptive capacity as a mediator of the relationship between business analytics and rational marketing decisions, the authors analyzed data from 224 Brazilian retail companies using structural equation modeling estimated with partial least squares. To test the cross-level moderation effect, the authors also performed a multilevel analysis in RStudio.

The authors found a partial mediation of the absorptive capacity in the relation between business analytics and rational marketing decisions. The authors also discovered that, in the MSMEs firms’ group, even if smaller companies find it more difficult to use data, those that do may reap more benefits than larger ones. This is due to the influence of size in how firms handle information.

The sample size, despite having shown to be consistent and valid, is considered small for a multilevel study. This suggests that our multilevel results should be viewed as suggestive, rather than conclusive, and subjected to further validation.

Rather than solely positioning business analytics as a tool for decision support, the authors’ analysis highlights the importance for firms to develop the absorptive capacity to enable ongoing acquisition, exploration and management of knowledge.

MSMEs are of economic and social importance to most countries, especially developing ones. This research aimed to improve understanding of how this group of firms could transform knowledge into better decisions. The authors also highlight micro and small firms’ difficulties with the use of marketing data so that they can have more effective practices.

The research contributes to the understanding of organizational mechanisms to absorb and learn from the vast amount of current marketing information. Recognizing the relevance of MSMEs, a preliminary multilevel analysis was also conducted to comprehend differences within this group.

Higher educational institutions, such as universities of applied sciences, have a significant role in promoting progress towards a sustainable future as defined by the United Nations (UN) sustainable development goals (SDGs). This paper aims to identify how the UN SDGs are featured in master’s theses set in work–life contexts.

Using a descriptive review and content analysis, this study identified the number of SDGs appearing in 31 master’s theses. Sustainable development (SD) and corporate social responsibility were reflected using the approaches and models in the literature. Finland’s eight objectives for committing to SD were used to examine the commitments made by the business school of the university of applied sciences to achieve Agenda 2030.

Emphasising the value of higher education for SD, this study found that SDGs three, eight and 12 appeared most frequently in the theses. Sustainable and responsible dimensions reflected several issues concerning both the worlds of business and industry among the firms and organisations investigated by the master’s degree students in the business school at the Jyväskylä University of Applied Sciences.

This research holds practical and pedagogical value, serving to encourage master’s and PhD students to further explore research on SDGs and to shape public policy.

Sustainability was looked at in a new way as investigated by the theses. Ways to integrate the SDGs into management degree programmes and conduct research in the fields of business administration, tourism and hospitality management were identified.

The increasingly active data practice in academic environments makes investigating college faculty users’ potential needs for library data services (LDS) essential. Guided by a conceptual framework rooted in the data lifecycle and the extended technology acceptance model, this study aims to investigate the relationship between faculty’s data engagement (DE) and their attitudes toward multiaspect LDS.

An online survey at a master’s college was conducted to collect data regarding faculty data practice, potential needs for data services (DS) and attitudes toward multiaspect LDS. Based on 139 complete and valid responses, the study built three conceptual models to demonstrate faculty users’ potential acceptance of LDS for research and teaching.

Participants’ research and teaching-related DE and background factors directly or indirectly affect their attitudes toward general DS, an institutional data repository if available and repository-based data curation.

The study contributes to DS and librarianship research by offering three conceptual models to explore LDS’ holistic support for faculty research and teaching. Moreover, the study provides insights into faculty’s job-related DE factors and calls for future research on effective DS in more college communities.

The variance between the winning bid and the owner's estimated cost (OEC) is one of the construction management risks in the pre-tendering phase. The study aims to enhance the quality of the owner's estimation for predicting precisely the contract cost at the pre-tendering phase and avoiding future issues that arise through the construction phase.

This paper integrated artificial neural networks (ANN), deep neural networks (DNN) and time series (TS) techniques to estimate the ratio of a low bid to the OEC (R) for different size contracts and three types of contracts (building, electric and mechanic) accurately based on 94 contracts from King Saud University. The ANN and DNN models were evaluated using mean absolute percentage error (MAPE), mean sum square error (MSSE) and root mean sums square error (RMSSE).

The main finding is that the ANN provides high accuracy with MAPE, MSSE and RMSSE a 2.94%, 0.0015 and 0.039, respectively. The DNN's precision was high, with an RMSSE of 0.15 on average.

The owner and consultant are expected to use the study's findings to create more accuracy of the owner's estimate and decrease the difference between the owner's estimate and the lowest submitted offer for better decision-making.

This study fills the knowledge gap by developing an ANN model to handle missing TS data and forecasting the difference between a low bid and an OEC at the pre-tendering phase.

This study is focused to support an ongoing development project of the case company's current state and the challenges of the order-to-cash (O2C) process. The O2C process is the most visible process to the customer, and therefore, its punctual and fluent order management is vital. It is observed that the high degree of manual work in the O2C process causes mistakes, delays and rework in the process. The purpose of this article is therefore to analyze the case company's current state of the O2C process as well as to identify the areas of development in this process by deploying the means of Lean Six Sigma tools such as value stream mapping (VSM).

The study was conducted as a mix of quantitative and qualitative analysis. Based on both the quantitative and qualitative data, a workshop on VSM was organized to analyze the current state of the O2C process of a case company, engaged in the energy and environment sector in Finland.

The results found that excessive manual work was highly connected to inadequate or incorrect data in pricing and invoicing activities, which resulted in canceled invoices. Canceled invoices are visible to the customer and have a negative impact on the customer experience. This study found that by improving the performance of the O2C process activities and improving communication among the internal and external stakeholders, the whole O2C process can perform more effectively and provide better customer value.

The O2C process is the most visible process to the customer and therefore its punctual and fluent order management is vital. To ensure that the O2C process is operating as desired, suitable process performance metrics need to be aligned and followed. The results gathered from the case company's data, questionnaire interviews, and the VSM workshop are all highlighted in this study. The main practical and managerial implications were to understand the real-time O2C process performance, which is necessary to ensure strong performance and enhance continuous improvement of the O2C process that leads to operational excellence and commercial competitiveness of the studied case company.

Micro and small enterprises (MSE) play a critical role in the Swiss economy but had no meaningfully adopted working from home (WFH) policy before the COVID-19 crisis. The timing of the study’s data collection allowed a unique assessment of Swiss MSEs’ adoption of WFH enabled by the adoption of digital technologies due to the first government-mandated COVID-19 lockdown. The study also set out to assess the permanence of any changes in the adoption of WFH by MSEs after initial government COVID-19 restrictions ended.

The study uses a threefold theoretical framework combining social, technical and spatial dimensions. Data were collected via telephone interviews. The utilised sampling frame included 153,000 small businesses with 4–49 employees, and the realised sample for the study was 503 interviews with MSE owners and managing directors (MDs).

The Swiss government’s COVID-19 crisis lockdown policies accelerated the digital transformation of work by employees in Swiss MSEs by increasing the number of employees WFH. However, the number of MSEs with WFH employees decreased after the first lockdown ended. Small business leadership is an important influence on the persistence of any increases in WFH.

The data collection uniquely captures the effects of externally driven digital transformation of work in small businesses by the adoption of WFH. The findings show that small businesses can rapidly learn new ways of working and support the claim that Swiss MSE MDs play a critical role in the adoption of WFH. They also confirm the importance of digital leadership and culture for realising the potential of WFH in small businesses.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The present article draws from the behavioral theory of the firm, and it explores whether various dimensions of organization slack can be employed as variables to measure organizations’ antifragility during times of uncertainty such as the Covid-19 pandemic. Furthermore, considering the limitations and regulations put into place during the most recent pandemic, the present study seeks to explore the moderating effect that collaborative networks might have on the relationship between various dimensions of organizational slack and firms performance.

The present study retrieves data from Thomson Reuters Data Stream, and it gathers observations from manufacturing companies located in Europe. The dataset is composed of observations spanning from the fiscal year 2019–2022. Consequently, through the use of a balanced panel data, the authors conduct multiple regression analysis.

The obtained empirical findings reveal that high discretion slack has a positive effect on companies performance whereas low discretion slack has a negative effect on their performance. Additionally, the obtained findings indicate that low levels of reliance on collaborative networks positively moderates the relationship between organizational slack and firms’ performance. On the other hand, high levels of reliance on collaborative networks negatively moderate the relationship between organizational slack and firms performance.

This manuscript carries several original contributions. It expands the literature stream concerning antifragility and collaborative networks. Additionally, it postulates an operational measure which can be used to indicate firms’ antifragility.

This study aims to examine how couplepreneurs foster an entrepreneurial mindset in their kids.

A qualitative research approach with semi-structured interviews was used as the data collection technique. Narrative analysis was conducted on a sample of 20 couplepreneurs in Mthatha, South Africa.

Narratives of how couplepreneurs foster an entrepreneurial mindset in their kids included purchasing toys and games for kids that encourage entrepreneurship; competition and team activities among kids that are related to entrepreneurship; the piggy bank; encouraging kids to read entrepreneurial books; and kid entrepreneur showcases.

Sample size challenges are a notable limitation, including research being conducted in only one province of South Africa. Caution is advised when attempting to generalise the results to other contexts.

Understanding the strategies used by couplepreneurs to instil an entrepreneurial mindset in children can help parents to influence and encourage their children's entrepreneurial growth, resulting in more creative and innovative people who make a positive contribution to society, economy and the community.

While there is a body of literature on couple entrepreneurship, there are shortcomings in studies examining how coupleprenuers in African countries instil an entrepreneurial mindset in their children. As a result, this study aims to complement the current corpus of African literature on entrepreneurship, particularly in the context of South Africa.