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Though certain characteristics of micro-firms affect the likelihood of their participation in external relationships, how cooperation in craft enterprises differs from low and high-tech enterprises has not been investigated yet. Therefore, this study aims to fill the above gap in the literature.

This study adopts a descriptive approach by extensively reviewing relevant literature to explore the unique characteristics and nature of micro-firm's co-operative behavior. The theoretical approach of this research is grounded in resource-based view and dynamic capabilities theories.

This study finds that handicraft micro-firms possess special and unique characteristics that differentiate them from low- and high-tech firms. Further, handicraft micro-firms' co-operative behavior also differs from other firms in terms of cooperation motives, breadth, depth and factors that inhibit or promote cooperation. Additionally, in small handicraft firms, the co-operation is more informal, personal and through social networks, whereas in the corporate sector, it is more formal, direct and through supply chains. This study also argues that contrary to handicraft and low-tech firms, high-tech firms are more likely to cooperate with external partners and invest heavily in R&D for new product development (often radical in nature).

This study enriches our understanding of handicraft micro-firms' special and unique characteristics that differentiate them from low- and high-tech micro-firms. This research also provides in-depth knowledge to understand the handicraft micro-firms’ co-operative behavior and how it differs from low- and high-tech firms.

Gamification has emerged as a dynamic force in education, with increasing interest in its impact on college students' learning. Most previous research regards gamification as a single element and only focuses on the cognitive level of gamification elements, lacking an overall exploration of the impact mechanism of gamification elements. Against the backdrop of virtual learning communities, we apply the cognition-affection-conation theory to examine the influence of various gamification elements on college students' online learning behaviors, examining both cognitive and affective pathways.

Data were collected through a predefined questionnaire from 11 Chinese virtual learning communities, with 587 respondents participating in the study. SmartPLS was employed to conduct a Partial Least Squares (PLS) analysis of the research model and test the hypotheses.

Our findings reveal that immersion and achievement-oriented gamification elements positively impact learning behavior. Conversely, the social gamification element exhibits a negative influence due to social burnout within virtual learning communities. This study pioneers a model to understand the intricate influence mechanisms of gamification elements on college students' online learning behaviors. The model contributes to the enriched exploration and practical application of college students' learning behaviors in virtual learning communities.

Unlike previous studies that often treat gamification as a single element and focus solely on cognitive aspects, this research explores both cognitive and affective pathways using cognition-affection-conation theory. By examining the influence of various gamification elements on college students' online learning behaviors in virtual learning communities, this study provides nuanced insights. In particular, immersion and achievement-oriented gamification elements positively impact learning behavior, while social gamification elements have a negative influence due to social burnout. This comprehensive approach deepens our understanding of how gamification affects students' learning experiences, enriches knowledge, and provides practical insights for educators and instructional designers.

As two essential styles of firm decision-making, the relationships among effectuation logic, causation logic and firm performance are unclear. It is helpful to deepen the understanding of reasoning theory and the process of decision-making. The purpose of this paper is to explore the relationship between effectuation logic, causation logic and firm performance.

Based on 31 independent empirical studies (including 11,600 samples) published by predecessors, meta-analysis is used to systematically integrate the impact of two decision-making styles on firm performance and explore the potential factors affecting their relationship.

The results show a positive correlation between two decision-making styles and firm performance and the influence of effectuation decision-making style in firm performance is slightly stronger. However, the application environment is different: in the emerging market, the causation decision-making style is more effective for firm performance management. When the firm chooses the effectuation decision-making style, it is more effective for performance management in the emerging market. In addition, the industry type, firm performance evaluation tools, national development level and firm scale and firm age can significantly moderate the impact of two decision-making styles on firm performance.

Both decision-making logics are possible ways for firm to success. Still, the future needs to dig deeper into the black box that can unlock the decision-making styles to achieve firm performance or competitive advantage based on other factors of the decision-behavior-outcome business model, more longitudinal data and experiments.

To the best of the authors’ knowledge, this is the first study to explore the impact of decision-making styles (effectuation logic and causation logic) on firm performance using a meta-analysis.

Risk perception is an essential factor affecting how individuals evaluate risk, make decisions and behave. The impact of risk perception on customer purchase behavior has been widely studied; however, the association has been debated. Therefore, the purpose of this paper is to examine the relationship between risk perception and customer purchase behavior and to examine factors that could moderate it.

This study conducted a meta-analysis of this relationship and examined factors that could moderate it. Six databases were comprehensively searched. Two reviewers independently selected the studies for inclusion, extracted data and assessed quality. Pearson's r was used as the effect estimate. A total of 33 studies were included in the meta-analysis.

The results revealed a negative relationship between risk perception and customer purchase behavior. The geographical region, purchase channel and country development level affected the relationship. The correlation between perceived risk and purchase behavior in European consumers was the highest, followed by the correlation in American consumers; the weakest correlation was found in Asian consumers. For consumers in developed countries, perceived risk had a stronger negative influence on customer purchase behavior than that for consumers in developing countries. The perceived risk of online purchase channels had a stronger negative impact on customer purchase behavior than that of offline purchase channels.

Risk perception is a useful context in which to explain barriers to customer purchase behavior. In addition, reducing consumers’ risk perception and perfecting the market transaction process with respect to buying behavior should be further studied.

The findings of this review indicate a direct negative relationship between risk perception and customer purchase behavior. To the best of the authors’ knowledge, this review is the first to meta-analytically summarize the impact of risk perception on customer purchase behavior in social sciences research, and it also illuminates new perspectives for future studies.

Based on self-consistency theory and conservation of resource theory, this study aims to discuss the impact of career calling congruence on employees’ innovation performance (IP) and analyzes the mediating effect of work passion [harmonious passion (HP) and obsessive passion (OP)].

To avoid serious common method biases, data in this paper were collected at three-wave. This paper investigated 381 employees to assess their career calling in time 1, measured their work passion in time 2 and assessed the IP of these employees in time 3. This paper also conducts confirmatory factor analysis, polynomial regression, response surface analysis, bootstrapping test and simple slope test to verify the research hypothesis in this paper.

In the career calling congruence case, employees’ HP, OP and IP are higher when both levels of serving oneself career calling and helping others career calling are high than when both are low; In the career calling incongruence case, employees’ HP, OP and IP are higher in the “low serving oneself and high helping others” case than in the “high serving oneself and low helping others” case; The more congruent the “serving oneself” and “helping others” career calling are, the higher the employees’ HP, OP and IP will be; and HP and OP mediate the relationship between career calling congruence and IP.

This study further clarifies the structure of career calling and find the positive effects of career calling on IP. The results present a deeper understanding of career calling and are universal applicable to the eastern culture context.

The research paper examines the impact of perceived social media marketing activities (SMMAs) (interaction, entertainment, customization, trendiness and word of mouth (WOM)) on customer loyalty (CL) toward e-commerce providers. The study also explores the mediating role of customer relationship quality (CRQ) (commitment, trust and satisfaction) on the relationship between perceived SMMAs and CL.

The study is based on the S-O-R model, which states that characteristics of the environment (stimulus) arouse a cognitive state (organism) that results in positive or negative behavior (response). The present study proposes the characteristics of the e-commerce environment as stimuli (S), the inner state of customers as an organism (O) and consumer behavior as the response (R). This study investigated the responses of 487 social media users through structural equation modeling (SEM).

The results offer three crucial findings. First, the study validated that perceived SMMA comprises five dimensions (interaction, entertainment, customization, trendiness and WOM) in the Indian e-commerce context. Second, perceived SMMA significantly influences CRQ (commitment, trust and satisfaction). Third, CRQ significantly mediates the relationship between perceived SMMA and CL.

The study attempts to understand the effect of perceived SMMA on CL via CRQ in an e-commerce context, especially in an emerging economy like India. The present study argues that the SMMA of e-commerce is likely to be reflected in CL when the consumers experience CRQ through commitment, trust and satisfaction. Thus exploring the mediating role of CRQ is the authors' contribution.

This paper aims to propose a multi-dimensional hierarchical K-means clustering algorithm for the purpose of intrusion detection. Initially, the clustering set of rules is proposed to shape some of clusters in the network and then the most beneficial clusters are decided on by the use of Cuckoo search optimization set of rules. Finally, an Artificial Bee Colony primarily based selection tree (ABC-DT) classifier is rented to classify the regular and unusual instances present in the network with the aid of the extracted features.

Intrusion detection system (IDS) is crucial for the network system; the intruder can take sensitive details about the network. IDS are said to be more effective when it has both high intrusion detection rate and low false alarm rate. Numerous strategies including gadget mastering, records mining and statistical techniques were tested for IDS mission. Recent study reveals that combining multiple classifiers, i.e. classifiers ensemble, can also own better performance than unmarried classifier. In this paper, a comparative study is conducted of the overall performance of four classifiers, i.e. hybrid ABC-DT particle swarm optimization-based K-means clustering (PSO-KM), help vector device (SVM) and K-Nearest neighbour (KNN). All the four classifiers are tested with exceptional packet sizes 1470, 1024, 512 and 256. The experiment is carried out for the speed ranging from turned into done for the velocity ranging from 250Mbps, 500Mbps, 750Mbps, 1.0Gpbs, 1.5Gbps, and 2.0Gbps in terms of accuracy, detection charge, specificity, false alarm charge and computational time. The experimental results reveals that the hybridization of classifiers performs better than the base classifiers in all scenarios.

This study analyses the performance of hybrid ABC-DT classifier and compares the performance against three well-known classifiers such as PSO-KM, SVM and K-NN. The performances of all the four classifiers are tested with Discovery in Data Mining (KDD) CUP 99 dataset with different packet sizes 1470, 1024, 512 and 256. The results show the classifier performance variations with different speed ranges. From the experimental results and analysis, the hybridization of classifiers such as ABC-DT outperforms the base classifiers in all scenarios.

The novel approach in this paper is used to study the hybrid ABC-DT classifier and compare the performance against three well-known classifiers such as PSO-KM, SVM and K-NN. The discussed concept is used within the network to monitor the traffic to and from all the devices connected in that network.