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This study aims to explore the direct and indirect effects of sales opportunism and sales conflict as well as of non-economic and economic satisfaction in business-to-business (B2B) sales relationships. This understanding offers B2B buyers enhanced knowledge of sales business expectations towards sustainable business relationships in the future.

Through self-administered questionnaires, data were obtained from 237 sales or marketing managers/directors of small- and medium-sized companies across industries in Spain, who were randomly contacted via LinkedIn. The multivariate analysis of measurement and structural models was based on IBM SPSS Amos 27.

The study confirms that sales opportunism positively affects sales conflict. Moreover, sales opportunism is negatively associated with non-economic sales satisfaction, whereas non-economic sales satisfaction is positively associated with economic sales satisfaction. Consequently, if all associates are pleased with the relationship and the gains it can provide, a long-standing orientation can be achieved.

The study expands existing theory on seller–buyer relationships in a B2B context. It contextualises direct and indirect relationships between two antecedents (sales opportunism and sales conflict) and two postcedents (economic sales satisfaction and non-economic sales satisfaction) in sales business–buyer settings.

The study guides buyers in B2B relationships towards an improved understanding of how sales businesses perceive opportunism and conflict (as negative precursors) to impact non-economic satisfaction and how it can influence economic satisfaction.

Most studies explore B2B relationship building from the perspective of the buyer, thereby creating a shortfall in developing an understanding of all partner expectations in B2B relational intent. Moreover, the measurement of satisfaction as a multidimensional construct secured the integration of non-economic satisfaction and economic satisfaction within a single model allowing the constructs measured in this study to be holistically assessed.

The efficiency of an educational program on entrepreneurial competence, Training the Potential Entrepreneur. Generation of an Educational Model for Entrepreneurial Identify (PEIEO) is evaluated in this study.

Pre and post intervention tests were administered to an Experimental Group (EG) and a Control Group (CG). Moreover, four hypotheses are proposed (H1, H2, H3, H4) and tested on a sample of 1036 Spanish students. The following instruments were applied: Attitude Towards Entrepreneurship-Spanish adaption; Measurement Scale of Personal Initiative in Educational Settings and Scale of General Self-Efficacy. ANCOVA and the Student's t-test were applied to the results.

The results show that training in entrepreneurial identity increases the entrepreneurial potential of young people (H1). A notable increase in proactivity and being a self-starter was observed with regard to personal initiative within the EG, and for self-efficacy (H3) both of which were predictors of entrepreneurial identity. Gender was likewise a predictor (H4).

Young people attending the PElEO training program in entrepreneurial potential increased their levels of entrepreneurial identity, thereby confirming the effectiveness of the program.

The program (PEIEO) is based on the development of entrepreneurial potential, a dimension that generates entrepreneurial identity (creativity, leadership, achievement and personal control).

This paper aimed to study business model innovation by a work-integration social enterprise (WISE). Specifically, the study investigated how the organization developed novel value propositions and created and delivered value for multiple stakeholders.

An in-depth qualitative study was conducted at Foreword, a for-profit organization that uses persons with disabilities, mental health conditions and special needs. Data was drawn from semi-structured interviews with stakeholders of the organization and several secondary information sources.

The authors’ inductive analysis revealed the existence of an innovative and powerful business model that is integrated by the organization’s overarching social mission and anchors its ability to deal with multiple conflicting logics such as economic, social, ecological sustainability and community development, to co-create value with and for multiple stakeholders.

The study underscores the need for business model innovation through enhancing value creation for multiple stakeholders for for-profit WISEs. Since the analysis and resulting model in the study are based on a single organization in a geographically small, affluent country with a hands-on government, they may need to be modified before applying in other contexts.

The study identifies several pointers for other social enterprises – specifically the need for managers to build business models appropriate for their organizational and environmental contexts.

The study’s originality stems from the adoption of a stakeholder lens to examine business model innovation. It also proposes an integrative conceptual model of the antecedents and outcomes of business model innovation.

In the wine industry, maintaining superior quality standards is crucial to meet the expectations of both producers and consumers. Traditional approaches to assessing wine quality involve labor-intensive processes and rely on the expertise of connoisseurs proficient in identifying taste profiles and key quality factors. In this research, we introduce an innovative and efficient approach centered on the analysis of volatile organic compounds (VOCs) signals using an electronic nose, thereby empowering nonexperts to accurately assess wine quality.

To devise an optimal algorithm for this purpose, we conducted four computational experiments, culminating in the development of a specialized deep learning network. This network seamlessly integrates 1D-convolutional and long-short-term memory layers, tailor-made for the intricate task at hand. Rigorous validation ensued, employing a leave-one-out cross-validation methodology to scrutinize the efficacy of our design.

The outcomes of these e-demonstrates were subjected to meticulous evaluation and analysis, which unequivocally demonstrate that our proposed architecture consistently attains promising recognition accuracies, ranging impressively from 87.8% to an astonishing 99.41%. All this is achieved within a remarkably brief timeframe of a mere 4 seconds. These compelling findings have far-reaching implications, promising to revolutionize the assessment and tracking of wine quality, ultimately affording substantial benefits to the wine industry and all its stakeholders, with a particular focus on the critical aspect of VOCs signal analysis.

This research has not been published anywhere else.