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Improving productivity and efficiency has always been crucial for industrial companies to remain competitive. In recent years, the topic of environmental impact has become increasingly important. Published research indicates that environmental and economic goals can enforce or rival each other. However, few papers have been published that address the interaction and integration of these two goals.

In this paper, we identify both, synergies and trade-offs based on a systematic review incorporating 66 publications issued between 1992 and 2021. We analyze, quantify and cluster examples of conjunctions of ecological and economic measures and thereby develop a framework for the combined improvement of performance and environmental compatibility.

Our findings indicate an increased significance of a combined consideration of these two dimensions of sustainability. We found that cases where enforcing synergies between economic and ecological effects were identified are by far more frequent than reports on trade-offs. For the individual categories, cost savings are uniformly considered as the most important economic aspect while, energy savings appear to be marginally more relevant than waste reduction in terms of environmental aspects.

No previous literature review provides a comparable graphical treatment of synergies and trade-offs between cost savings and ecological effects. For the first time, identified measures were classified in a 3 × 3 table considering type and principle.

This research focuses on analysing the effect of wine tourism on green product and process innovations developed by Spanish wineries. In addition, age, size and membership in a protected designation of origin (PDO) are introduced as control variables to increase the precision of the cause–effect relationship analysed.

The study proposes a conceptual model based on previous studies, which is tested using structural equations (partial least squares structural equation modelling [PLS-SEM]) with data collected from 202 Spanish wineries.

The research results show that wine tourism activity has a positive and significant influence on green product and process innovation.

The research contributes to the academic literature in several ways. First, the study advances knowledge and understanding of the benefits generated by wine tourism. Second, the research contributes to the literature that analyses the wine tourism–sustainability link, since it is predicted that this type of tourism can increase the capacity for green innovation. Third, to the best of the authors’ knowledge, there is no previous research that has analysed wine tourism as a catalytic variable for green innovation. Fourth, the proposed theoretical model has not been previously addressed in the academic literature, so the study represents an important advance in scientific knowledge.

The problem of environmental pollution is becoming increasingly severe, and international consensus confirms the need for eco-friendly consumption. Worldwide, the eco-friendly food market is booming, so understanding consumers’ motivations to purchase these foods is crucial. This paper aimed to construct a model explaining consumers’ intentions to purchase eco-friendly food by combining stimuli-organism-response (SOR) and signalling theories and exploring the mechanisms by which macro- and micro-signals impact perceptions of value and consumers’ subsequent willingness to purchase eco-friendly food.

An online questionnaire was distributed through the Qualtrics platform, and the completed questionnaires were collected in March and April 2023. The study used partial least squares structural equation modelling (PLS-SEM) to analyse the 331 valid responses received.

The results indicated that trustworthy eco-labels for high-quality and health-promoting products, as conveyed in macro signals, significantly enhanced consumers’ perceptions of functional value. The peer effect and a moderate level of food anthropomorphism conveyed in micro-signals substantially improved their perceptions of social value, whilst the perceived value of products significantly and positively influenced their purchase intentions.

This study explains consumers’ motivations to purchase eco-friendly products. This provides an explanation for the effect of macro- and micro-signals on value perceptions. By integrating the different dimensions of these signals to create a unified research perspective, the paper provides an integrated model, thereby filling a research gap concerning the influence of two-dimensional signals on purchase intention. By supporting eco-friendly food use, the paper contributes to environmental protection and sustainable development.

This research examines consumer reluctance to purchase organic food using the theory of innovation resistance and also extends the theory by investigating the moderating influence of eco-literacy. In addition, the authors used a multigroup analysis to identify differences between consumer segments.

Data collection used computer-assisted web interviewing and a prior screening process to confirm engagement. Through stratified quota sampling, 1,000 useable responses were obtained from 2,887 recipients.

The findings reveal barriers are significant inhibitors to adopting organic food. Among these barriers, usage, risk tradition and image barriers have a significant adverse influence on purchase intention. In contrast, the value barrier has a nonsignificant influence on the purchase intention of organic food. However, the study found that eco-literacy significantly reduces the negative influence of risk and tradition barriers on consumers' intentions. In addition, a multigroup analysis examines notable differences between consumer groups based on education, age and income.

This research has significant social implications for boosting sustainable consumption in Lithuania. It identifies key barriers to organic food adoption, emphasizing the need for strategic interventions. The study highlights eco-literacy as an essential tool in diminishing resistance to organic food, advocating for targeted educational initiatives. Additionally, it reveals the importance of tailored marketing strategies based on different consumer demographics. Overall, this study provides important insights to promote environmentally conscious consumer behavior and overcome resistance to innovation in the organic food sector.

This study expressively advances the understanding of intentional behavior by exploring organic food within Lithuania's Baltic economy. It authenticates the innovation resistance theory's applicability to organic food behavior in the region while emphasizing the moderating impact of eco-literacy in the link between barriers and purchase intention concerning organic food. Furthermore, using advanced methods such as partial least squares statistical modeling and multi-group analysis, the research reveals how barriers affect the purchase intention of organic food among different groups of consumers.

Green practices are essential for sustainability. However, it is challenging due to the socioeconomic and environmental concerns. Similarly, after the induced SDG-12 and SDG-13 by United Nations, the pressure groups forced manufacturers to consider sustainability. Therefore, this research aims to examine the sustainability through multifaceted green functions in manufacturing is examined.

Data were collected from 293 supply chain professionals of manufacturers from a developing economy. Hypotheses were tested through a quantitative method using partial least squares-structural equation modeling with the help of SmartPLS version 4 to validate the measurement model.

The findings revealed that all six direct hypotheses were supported. However, out of four hypotheses of mediation, one was not supported. Besides, a sequential mediation of green supply chain environmental cooperation and green human resource management was supported. The findings illustrated that green supply chain practices positively influence all used variables.

This research provides practical insight to practitioners to implement green practices in their supply chain networks for social, economic and environmental sustainability and compliance with SDG-12 and SDG-13. The sustainability was validated in a higher-order construct (HOC) (formative), including sequential mediation in the model with the support of resource dependency theory. Therefore, this study adds substantial literature to the existing body of knowledge.

This research provides an interdisciplinary framework by adding knowledge to the Resource Dependency Theory to address Sustainable Development Goals-12 (SDGs) and SDG-13. Likewise, this research provides an extension towards the body of knowledge on the issue, which can be used in future research and critical examinations for cleaner and sustainable production. So far, in Pakistan, no research has looked at the function of these integrated variables in the manufacturing industry with a diligent focus on sustainability as it was validated in a higher-order construct (formative) with one sequential mediation, which makes this research unique.

This study aims to explore the role of the green market (GM) and green innovation (GI) towards green entrepreneurship (GE) and sustainable development (SD).

Based on cross-sectional data, the researchers used quantitative methods in this study to confirm the conceptual framework. The researchers used a questionnaire to collect the data obtained from Pakistan's knowledge-based companies (KBCs). In total, the researchers used 192 usable samples to deliver the findings.

The researchers used structural equation modeling (SEM) to ensure the model's fitness and as a basis for this study's hypotheses. The findings highlight that the GM factors, such as green product (GP), green design (GD), green supply chain (GSC) and green production (GPN) have a positive and significant effect GM factors, such as on both GE and SD. Further, GI is, also, a significant predictor of GE and SD. Finally, this study's findings show that GE has a predictive role of towards SD.

This study's findings create a source of attention for individuals to preserve the GM's natural resources. Further, mainly in developing contexts like Pakistan, the addition of the GI factor and the GM towards GE and SD contribute to the depth of the existing literature.

By integrating factors, such as innovation toward GE and SD, this study's findings provide an original contribution to the empirical evidence.

This study empirically investigates the impacts of technological innovation and operational efficiency on environmental performance and the moderating effects of environmental orientation.

We develop a conceptual framework based on the Porter Hypothesis. We collect a sample of 850 listed firms in China between 2010 and 2019. The fixed effect model was used to analyse the data.

The empirical findings reveal that technological innovation indirectly enhances environmental performance through operational efficiency and partially mediates this impact. We also find that environmental orientation strengthens the positive impacts of technological innovation and operational efficiency on environmental performance.

This study contributes to the literature by revealing that technological innovation is positively associated with operational efficiency and environmental performance, which suggests that technological innovation can simultaneously enhance business and environmental performance. Hence, this study provides empirical support for the Porter Hypothesis. The results also extend the Porter Hypothesis by revealing how technological innovation affects environmental performance and under what conditions technological innovation has a greater impact on environmental performance.

The psychological foundations of consumers’ reasons for product choices are analyzed in the field of marketing. The purpose of this research is to identify the implicit reasons for white meat consumption in the UK and Turkey.

In the scope of the means-end chain theory, in-depth interviews were conducted with individuals, and the reasons for consumers’ product preferences were revealed by moving from concrete to abstract.

It has been determined that the white meat consumption of Muslims in the UK is primarily shaped by their religious approach. In Turkey, on the contrary, both consumption patterns and reasons for preference are changing. It has been found that white meat consumption is associated with values such as security needs, satisfaction with life, self-fulfillment and happiness.

This research has contributed to the marketing literature by examining consumers’ implicit consumption reasons for white meat in the context of religion and culture.

Marketing strategies should focus on building trust in halal certification, particularly in the UK. Brands should associate their promotion strategies with feelings of security and happiness, which are associated in the minds of consumers.

This study is a new study in terms of revealing the connotations of consumers about consuming chicken and fish and showing the implicit needs that the brands can emotionally associate with.

The adoption of residential rooftop solar panel systems (SPS) in India is at a nascent stage. Therefore, this study aimed to examine the factors affecting consumers’ intention to purchase SPS by expanding the theory of planned behavior (TPB) with three environmental psychology factors. The study was targeted at potential users’ intention to purchase SPS, thus it further explored the moderating role of perceived government subsidy policy (PGSP) in determining consumers’ purchase intention of SPS.

Using G*power software, the minimum sample size of 189 was calculated; accordingly, 292 valid responses were gathered from potential users of SPS from three Indian states, namely Rajasthan, Punjab and Haryana, via an online questionnaire survey with the help of purposive sampling method. Structural equation modeling technique of partial least squares was employed to analyze the data.

Results demonstrated that attitude, subjective norms, perceived behavioral control, perceived consumer effectiveness (PCE) and PGSP significantly influence purchase intention of SPS. Green trust and green self-identity did not influence the purchase intention of SPS. Further, PGSP strengthens the effect of attitude, green trust, PCE on purchase intention of SPS while it weakens the effect of subjective norms on purchase intention of SPS.

This study contributes to the existing literature by integrating green trust, green self-identity, PCE and PGSP into the TPB model to better understand factors affecting consumers’ purchase intention towards SPS in India.

We propose a machine learning based methodology to deal with data collected from a mobile application asking users their opinion regarding fashion products. Based on different machine learning techniques, the proposed approach relies on the data value chain principle to enrich data into knowledge, insights and learning experience.

Online interaction and the usage of social media have dramatically altered both consumers’ behaviors and business practices. Companies invest in social media platforms and digital marketing in order to increase their brand awareness and boost their sales. Especially for fashion retailers, understanding consumers’ behavior before launching a new collection is crucial to reduce overstock situations. In this study, we aim at providing retailers better understand consumers’ different assessments of newly introduced products.

By creating new product-related and user-related attributes, the proposed prediction model attends an average of 70.15% accuracy when evaluating the potential success of new future products during the design process of the collection. Results showed that by harnessing artificial intelligence techniques, along with social media data and mobile apps, new ways of interacting with clients and understanding their preferences are established.

From a practical point of view, the proposed approach helps businesses better target their marketing campaigns, localize their potential clients and adjust manufactured quantities.

The originality of the proposed approach lies in (1) the implementation of the data value chain principle to enhance the information of raw data collected from mobile apps and improve the prediction model performances, and (2) the combination consumer and product attributes to provide an accurate prediction of new fashion, products.