工商管理论文哪里有？由于本研究论文旨在调查尼日利亚在线品牌社区对消费者购买意愿的影响，因此收集了拉各斯州不同地区的男性和女性的回应，共有200名受访者。在本研究论文中，被调查者属于不同的年龄组、学历。大多数受访者为男性，年龄在18-24岁之间，具有一级学历。本研究设计并发放了一份封闭式问卷，测量了网络品牌社区影响力、社区承诺和消费者购买意愿的不同组成部分。
Chapter 1 Introduction
1.4 Ethical Issues
Ethics entails the provision of guidelines and measures to guide the research process from the beginning to the end. Ethical codes applicable to this study entail integrity and honesty, objectivity, openness, respect for intellectual property and responsible use of academic resources. The use of full cited and referenced sources will confirm the acknowledged of borrowed text ideas from other authors. Also, privacy will be highly preserved; thus, consent forms will be duly filled by the participants, and no one will be coerced into participating in the project.
Chapter 3 Theoretical Framework and Hypothesis
3.1 Research Model
This research looks at three main features of the online brand community: Information sharing, community interactivity, and community rewards. The first two characteristics (Information Sharing and Community Interactivity) show a great influence on the satisfaction of community members and their community commitment. This study focuses on brand community characteristics and community operating mechanisms by community category, filling the gap between online community and marketing research. In an online brand community, consumer behavior depends on the quality of information relayed about the brand. In the environment in which members interact, quality of information entails their discernment of the quality of information available to them in comparison to their expectations and preexisting perception about the brand (Islam & Rahman, 2017). This may lead to a community commitment Certain factors determine the quality of information, including the relevance, access, interactivity, and the ability to customize the information. The availability of these elements influences customer engagement with the brand eventually influencing their consumer behavior, including intentions to purchase. However, the absence of these elements is likely to affect the quality of the information, thus affecting their ability to search and process it (Dessart et al., 2015). Members are likely to gain more benefits as they are likely to find the interaction appealing.
CHAPTER 5 RESULTS AND DATA ANALYSIS
5.1 Presentation of Tables and Interpretation:
Table 2 Showing the Analysis of Demographic of the Respondents based on Age.
From the above table, it can be deduced that most of the respondents in this study are between the age range of 18-24 years with a frequency of 87 (43.5%), followed by age range of 25-34 years with frequency of 43 (21.5%), (17.5%) with a frequency of 35 are between the age range of 35-44 years, while (10%) with frequency of 20 were within the age range of 45-54 years. Finally, respondents between the age 55 and above, had a frequency of 15 (7.5%). It is evident that respondents that fall within the age range of 18-24 years participated more in this study.
5.2 Structural Model
Structural model represents the theory that shows how constructs are related to other constructs. Structural part of the SEM model expresses the relationships among latent variables and disturbances (errors in the equations). Structural model is able to estimate the relationships among latent variables, is able to test overall model in addition to individual paths, and is able to model disturbances.
Based on the total effects table, community commitment has a positive impact on consumer purchasing intention because the P-value is 0.005.
Also, the above table shows that community interactivity has a positive impact on community commitment because the P-value is 0.035.
Also, we can see that community interactivity has a positive influence on consumer purchasing intention because the P-value is 0.023.
CHAPTER 6 DISCUSSION, CONCLUSION AND RECOMMENDATIONS
6.1 DISCUSSION
Online brand communities produce benefits to individuals and organizations (Cothrel and Williams 1999) through their members’ voluntary efforts. The possibility that affect, norms, and costs may influence these voluntary efforts has been discussed in the literature –although tangentially–but these have never been conceptualized as individual-community bonds that encourage specific behaviors. Our research not only integrates these into a system of group commitments, but it also emphasizes the importance of looking into a wide range of online behaviors, we built on previous research to create a more detailed model of people's interactions with their online communities. We also demonstrated that each form of commitment has unique explanatory power, and that these are not simply alternate explanations for the same thing. Indeed, past studies of online communities may well have over-stated the breadth of influence of each of these lines of motivational logic; in contrast, this study had produced highly discriminating results by clearly identifying which motivations produce particular kinds of online behaviors.
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