Discussion and Recommendations Sharing Economy

Discussion and Recommendations

The antecedents and outcomes linked to SE reveal significant diversities in how consumers SE integration in their lives. From January 2016 to July 2021, the SLR indicates that consumer factors such as demographics and social norms significantly contribute to SE. Product factors also affect SE as they determine the perception of the main physical characteristics. The third main element that constitutes the three primary influencers is the environmental factors. The SE effects emanating from environmental factors fail to attract significant attention owing to the amount of time taken to have the effects. For instance, negative environmental factors such as degradation are linked to long-term and consistent unfavorable usage of resources. Thus, the existing literature does not capture the essential factors hence a need for more research and their integration into the study. Indeed, the environmental factors that form the basis of the research constitute 4 out of the 150 outcomes hence significant deficiencies. Challenges in participation levels were also evident, implying that for better findings, particularly on outcomes, the research requires better integration of the relevant players.

The benefit of the research and interest among the players depends on how the participants feel about them (Machala, 2020). First, it is essential to note that some participants have not experienced a platform different from what SE offers. Consequently, they fail to acknowledge the power of SE, especially on online resources. The gains, especially on environmental conservation, are not measurable in the literature about Uber and overall car sharing. This is despite the significant role such factors could play in shaping the research outcome (Machala, 2020). People will react based on their surroundings, and the lack of comparison variables makes the research non-conclusive.

According to the literature in this research and future projections, the intensity of incorporation of SE since 2019 and, more specifically, during the pandemic increased, creating a new picture of the significance of SE. However, the research does not explore this development, implying that for reliability, there should be a deeper integration of the changes in SE to give more disparity in the antecedents and the outcomes. Thus, a more refined meta-analysis is essential to make the research more conclusive. Notably, the level of SE from 2019 has, to a great extent, been non-voluntary. Instead, the pandemic drove consumers into a different trajectory leading to economic effects that could change in the future.

For this reason, the statistics on the antecedents remain instrumental in shaping the research about the effects of SE on consumers' lives. A typical example of this effect is evident in the analysis of SE on the Chinese population. Ashworth (2000) explains that the change in attitude plays a major role in influencing SE. As noted in the analyses of the perceived characteristics, consumers develop expectations that influence how they interact with different resources. While these attitudes and perceptions play a crucial role in making decisions, the associated variable is not covered adequately. Indeed, only eight variables are examined in the five key articles. A deeper analysis of these influencing factors is recommended because they shape how consumers participate in SE. These characteristics and SLR drive many decisions for both antecedents and outcomes should integrate more variables to determine their contribution to participating in SE.

The chosen literature focuses on specific regions to derive generalized findings of consumers' interaction and response to SE. For instance, in examining the psychological factors that influence how consumers interact with SE, such as privacy and scarcity of resources, it is essential to integrate more geographical regions. Some responses to SE could be affected by cultural values, and their lack of consideration in the research gives a false impression about the obstacles. Waheed et al. (2022) explain that such variables are important in predicting behavioral intentions. Behaviors have direct effects on how consumers contribute to SE. Integrating such features is essential in predicting consumers' behavior, which helps enhance research generalization. Assessment of a few variables in a specific region can be used to make a generalized conclusion based on the outcome so behavioral theories.

Limitations and Opportunities for Further Research

According to the literature analyzed in this SLR, there are significant limitations in the outcomes recorded from consumer participants in SE. There are numerous factors in previous economies on SE that went uncovered. Consumers face undocumented challenges that make adopting corrective measures to streamline the SE-related factors challenging. For instance, the outcomes are significantly minimal compared to antecedents. The research fails to share consumers' gains using SE (Waheed et al., 2022). Instead, there is some bias in how consumers determine the benefits linked to SE. While economic and environmental benefits are linked to SE, the substantial valuation of these benefits is not quantified. As a result, the solutions to the problems linked to poor integration of SE go unrealized.

The research focused on participants who are active players in the sharing economy. Thus, it has some limitations because it lacks a point of comparison. More reliable findings should consist of control values where those consumers who avoid SE are included to provide the basis of comparison. The present nature of the research does not capture the psychological barriers of SE among this set the population, making it challenging to generalize the findings.

Another limitation is the degree of categorization and calculation of associated variables. The 11 common variables used in the research were not sufficient. This poses some limitations considering that since 2019, the use of SE has been significantly high. It means more variables were required to make the research more reliable in the present time. The broad nature of the research makes it challenging to derive clear results that reflect the actual influences of SE on consumers' lives.

The research gaps reveal various opportunities for future research. The gains linked to SE in the social settings require deeper analysis to establish the factors contributing to consumer social bonds. While SE focuses on the economic effects of resource utilization, indirect factors shape how resources are shared, influencing SE. For instance, social value is an important attribute that governs how consumers interact. Deep research on individual social values is important in determining the section of consumers who have a major contribution to the SE hence allowing for the determination of areas where such statistics should be generalized. One such area is the online engagements that form a significant part of this research. The research focuses on technologies that have a direct contribution to SE. However, the digital age has come with more technologies that impact SE. For instance, collaboration tools significantly affected resource sharing during the pandemic, which is part of SE. Jiao (2021) explains that SE, like those witnessed in car-sharing, is significantly affected by consumers' behavior. Equally, advanced technologies in other domains could depict similar characteristics hence a need for further research. The subjective nature of these behaviors should be examined too.

While technology is an essential consideration when analyzing SE, there is a wide gap in how similar effects are felt in regions that experience lower technological advancements. Besides, areas where SE-related technologies exist but the degree of integration into consumers' lives is minimal. In keeping with these considerations, future research should consider using SE by setting up control variables that separate unique characteristics that compel consumers to adopt a specific behavior. This way, the research faces limitations by assuming equal exposure to technologies among the participants. Consequently, the findings cannot be generalized, posing credibility questions.

The research employs quantitative coding in the analyses of 22 articles. Two limitations are evident in making this selection. There is a possible bias in quantifying qualitative values, such as behavioral responses. A researcher can assign different codes to these characteristics leading to varied results. Thus, the research should offer the influencing attributes to assign the codes. Secondly, in examining the consumer effects on SE since 2016, the chosen sample size is small, especially when it represents such wide geographical regions. The small sample size makes the findings less credible hence challenging to generalize them.