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Considering the relevance of understanding what influences environmentally sustainable consumer choices, the present study aims to examine and synthesize the key determinants factors from literature and outline a new conceptual framework for explaining green purchasing behaviors (GPBs).

A bibliometric analysis was conducted on 161 articles extracted from Web of Science and Scopus databases, which were systematically evaluated and reviewed, and represent the current GPB knowledge base. Content analysis, science mapping and bibliometric analysis techniques were applied to uncover the major theories and constructs from the state-of-the-art.

The evolving debate between altruistic and self-interest consumer motivations reveals challenges for rational-based theories, as most empirical applications are not focused on buying behaviors, but instead either on pro-environmental (non-buying) activities or on buying intentions. From the subset of leading contributions and emerging topics, nine thematic clusters are unveiled in this investigation, which were combined to create the new PSICHE framework with the purpose of predicting GPB: (P)roduct-related factors, (S)ocial influences, (I)ndividual factors, (C)oncerns about the environment, (H)abits and (E)motions.

By uncovering the multiple intervening factors in GPB decision processes, this study will assist practitioners and academics to move forward on how to foster more sustainable consumer behaviors.

The present study provides readers a summary of an unprecedentedly broad collection of papers, from which the key themes are categorized, the domain's intellectual structure is captured and an actionable framework for enhancing the understanding GPB is proposed. Four new thrust areas and a set of future research questions are included.

Petroleum hydrocarbons are naturally occurring flammable fossil fuels used as conventional energy sources. It has carcinogenic, mutagenic properties and is considered a hazardous pollutant. Soil contaminated with petroleum hydrocarbons adversely affects the properties of soil. This paper aim to remove pollutants from the environment is an urgent need of the hour to maintain the proper functioning of soil ecosystems.

The ability of micro-organisms to degrade petroleum hydrocarbons makes it possible to use these microorganisms to clean the environment from petroleum pollution. For preparing this review, research papers and review articles related to petroleum hydrocarbons degradation by micro-organisms were collected from journals and various search engines.

Various physical and chemical methods are used for remediation of petroleum hydrocarbons contaminants. However, these methods have several disadvantages. This paper will discuss a novel understanding of petroleum hydrocarbons degradation and how micro-organisms help in petroleum-contaminated soil restoration. Bioremediation is recognized as the most environment-friendly technique for remediation. The research studies demonstrated that bacterial consortium have high biodegradation rate of petroleum hydrocarbons ranging from 83% to 89%.

Proper management of petroleum hydrocarbons pollutants from the environment is necessary because of their toxicity effects on human and environmental health.

This paper discussed novel mechanisms adopted by bacteria for biodegradation of petroleum hydrocarbons, aerobic and anaerobic biodegradation pathways, genes and enzymes involved in petroleum hydrocarbons biodegradation.

Work-family conflict is an important topic which had an evolution, starting from a static definition, where work and family domains were divided, to a more dynamic and complex balance. COVID-19 has influenced society and created a significant distress among families and working activity, and this topic has been characterised by a major interest, considering some old definitions where this balance was considered problematic but not as an enriching opportunity.

The authors used SCOPUS to find all records mentioning work-family conflict, by considering book, article and review, excluding conference paper and considering only records written in English language. After a duplicated and not pertinent record removal, the authors obtained a number of 675 records. The authors considered 437 records from SCOPUS to create a cluster map.

Using SCOPUS and VOSviewer the authors have clustered 5 different areas, which are regrouped in next clusters considering keywords with most co-occurrence and significancy: Work-life balance and burnout gender cluster job stress and performance social and family support job satisfaction.

Cluster map is origined only by SCOPUS database.

This work aims to find a state of art about this topic, creating hypothesis where this problem has been exacerbated by 2020 due to important society modifications created by COVID-19, where recent evolution of work-family balance has been complicated by papers which come back to consider this balance as problematic.

Previous research suggests that the compensation offered to customers after a service failure has to be substantial to make customer satisfaction surpass that of an error-free service. However, with the right service recovery strategy, it might be possible to reduce compensation size while maintaining happy customers. The aim of the current study is to test whether an anchoring technique can be used to achieve this goal.

After experiencing a service failure, participants were told that there is a standard size of the compensation for service failures. The size of this standard was different depending on condition. Thereafter, participants were asked how much they would demand to be satisfied with their customer experience.

The compensation demand was relatively high on average (1,000–1,400 SEK, ≈ $120). However, telling the participants that customers typically receive 200 SEK as compensation reduced their demand to about 800 SEK (Experiment 1)—an anchoring effect. Moreover, a precise anchoring point (a typical compensation of 247 SEK) generated a lower demand than rounded anchoring points, even when the rounded anchoring point was lower (200 SEK) than the precise counterpart (Experiment 2)—a precision effect.

Setting a low compensation standard—yet allowing customers to actually receive compensations above the standard—can make customers more satisfied while also saving resources in demand-what-you-want service recovery situations, in particular when the compensation standard is a precise value.

The purpose of this paper is to incorporate Chinese traditionality (CT) and patriotism (PAT) within the theory of reasoned action (TRA). It tests the moderating effect of gender with the aim to provide a deeper understanding of why Chinese tourists choose to take domestic travels.

Data is collected from 370 Chinese tourists. Convenience sampling is used. Structural equation modelling is used to test the proposed hypotheses.

The results of this paper show that PAT is positively related to tourists’ attitudes (ATs) and Chinese domestic travel intention (CTI). Moreover, CT is found to influence PAT, ATs and subjective norms (SNs) directly, as well as CTI indirectly. However, the positive relationship between PAT and SNs is not supported. Additionally, the influence of PAT on CTI for females is significantly higher than that for males.

The current paper adopts convenience sampling; data is collected using an online questionnaire which may cause sample bias and even reduce the reliability of the data. Future studies may adopt quota sampling based on the population of each province to gain more reliable data. Further research can consider including more constructs to better understand why Chinese people choose to travel domestically.

This paper is one of the first attempts to include PAT and CT within the TRA and contributes to the pool of literature on the TRA. It provides a comprehensive understanding of CTI. Second, PAT and CT are linked to the TRA, which expands the application of PAT and CT to the context of hospitality and tourism. Finally, the moderating role of gender contributes to the knowledge regarding the moderating effect between their respective relationships.

性别在中国传统与爱国主义对中国国内旅游意愿影响中的调节作用

摘要

本研究将中国传统性与爱国主义引入理性行为理论, 同时将性别作为调节变量, 目的在于探究中国游客选择国内游的原因。

通过分析便利抽样所收集的370份中国游客样本, 运用结构方程模型验证本研究的假设。

中国游客爱国主义能够正向显著影响其国内游的态度和旅游意向; 此外, 中国传统性也直接影响游客的爱国主义、态度和主观规范, 并且分别通过爱国主义、态度和主观规范间接影响旅游意向; 然而, 爱国主义和主观规范之间的关系却并没有得到验证; 最后, 女性游客的爱国主义对于旅游意向的影响作用显著高于男性游客。

首先, 本研究运用网络调研的方式进行便利抽样, 这一点有可能产生样本偏差, 甚至降低了样本的可信度, 未来研究可以根据各省人口数量采用配额抽样的方式进行抽样, 以期进一步提高数据的可信度; 其次, 更多的变量应当被引入研究, 以进一步探究中国游客选择国内游的原因。

首先, 本研究是为数不多的将爱国主义和中国传统性引入理性行为理论, 这一点进一步拓展了关于理性行为理论的研究范围, 也进一步加深了对于国内游原因的认识; 其次, 将爱国主义和中国传统性这一概念引入旅游领域, 进一步拓展了关于两者研究的边界; 最后, 在中国国内游的研究领域中, 将性别作为调节变量引入本研究一定程度上填补了在该领域研究中的不足。

La influencia de la moderación de género en la tradición China y el patriotismo en la intención de viajar dentro de China

Este research incorpora los conceptos a de la tradicionalidad China (TC) y el patriotismo (PAT) a la teoría de La Acción razonada (TAR), teniendo en cuenta el efecto moderador de género, con el objetivo de profundizar en la comprensión de porqué los turistas chinos eligen realizar viajes domésticos/nacionales.

A partir de los datos recolectados de 370 turistas chinos utilizando las muestras de cuestionarios realizados de manera on-line, éste estudio usa un modelado de ecuaciones estructurales para probar las hipótesis propuestas.

Los resultados demuestran que el PAT está positivamente relacionado con las actitudes del viajero y la intención de viaje nacional chino (IVNC).Es más, la tradicionalidad China (TC) influye en el Patriotismo (PAT), las actitudes del viajero chino (AVC) y también en las normas subjetivas (NS) directamente.Adicionalmente, la influencia del PAT en la intención de viaje del viajero doméstico chino, especialmente en mujeres, es significativamente mayor que en hombres.

Primero, el estudio adopta un muestreo de conveniencia y recopila cuestionarios on-line, lo que puede causar un sesgo en la muestra e incluso reducir la confiabilidad de los datos obtenidos.Los futuros estudios pueden adoptar un muestreo por cuotas basado en el número de población de cada una de las provincias de China, para obtener datos más relevantes.

Este estudio es uno de los primeros en incluir el PAT y el TC dentro de la TAR, que amplía la literatura sobre la TAR y proporciona una comprensión más completa de las actitudes del viajero chino.Segundo, el PAT y la TC están vinculados al TAR, el cuál expande la aplicación del PAT y la TC en el contexto del turismo en todas sus ramas.Por último, el rol moderador de género contribuye al conocimiento, sobre el efecto moderador entre sus respectivas relaciones.

There is little empirical evidence on how blockchain affordances may encourage consumers to make sustainable choices. Thus, this paper examines how blockchain affordances affect consumers’ sustainable consumption.

We focus on three blockchain affordances: transparency, traceability, and immutability in this paper. By integrating the affordance lens and theory of consumption values (TCV), we develop a research model wherein we posit that blockchain affordances influence several consumption values, which then affect consumers’ intention to purchase sustainable products. In the study, we designed a scenario and user interface for a novel blockchain-based app for sustainable consumption in the context of the fashion industry and surveyed 295 European consumers to examine the study’s research model. We then analyzed the collected data using the partial least squares technique.

The results show that blockchain affordances positively affect consumption values, including efficiency, social impression, trust, and sustainability information clarity. In turn, these values influence the consumers’ purchase intention of sustainable products. Additionally, our post hoc analysis shows that these consumption values fully mediate the effect of blockchain affordances on consumers’ purchase intention, where trust and sustainability information clarity is found to have a higher impact.

Empirical research studies focusing on understanding blockchain’s effect on sustainable consumption values have been limited in prior literature. This study, drawing on the affordance lens, proposes distinct blockchain affordances and empirically validates their impact on consumers’ sustainable purchase intention. By integrating TCV, it highlights the mediating mechanism that drives blockchain’s impact on consumers’ purchase intention. We empirically identify the values that mediate the effects of blockchain affordances on consumers’ purchase intention; further, we discuss implications for research and practice based on the study findings.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

Satisfaction and loyalty as vital and strategic concepts in the marketing literature are highly important to companies and marketers. The review of the existing literature reveals a gap of the role of emotional constructs that can begin in a regular and rational sequence of satisfaction and ultimately lead to the formation of consumer loyalty. Hence, this study aims to answer the question of whether emotional constructs such as emotional attachment and love play a mediating role in the process of transitioning from satisfaction to loyalty in the correct sequence.

A total of 300 valid questionnaires on smartphone and apparel brands were collected from respondents and analyzed using the partial least squares method.

The results showed that brand love is the strongest antecedent of brand loyalty and is the only variable that directly influences brand loyalty in comparison to satisfaction and emotional brand attachment. Moreover, the examination of indirect effects revealed that our assumption based on that the emotional structures such as emotional attachment and brand love play a mediating role in the process of transitioning from satisfaction to loyalty in a correct sequence is supported.

Generalizability needs to be established with a wider range of consumer groups. The survey was conducted in Iran, and future research should assess the same product categories in other cultural settings as well as consider other product categories to assess the external validity of these results. The insights on consumers’ brand relationships help brand managers devise effective brand management strategies.

The managerial implications can guide managers toward enhancing the consumers’ loyalty to the brand through a better understanding of the consumer loyalty process to a brand as well as better relational marketing practices.

The study validates the mediating role of emotional brand attachment and brand love in the relationship between brand satisfaction and brand loyalty, is one of the first to develop a conceptual model that examines the role of emotional structures in the process of transition from satisfaction to loyalty, is one of few studies to develop the role of emotional structures in the form of a relational chain of brands in the process of transition from satisfaction to loyalty.