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Business Models Their Resilience In Contingencies Term Paper

Review of "Business continuity of business models: Evaluating the resilience of business models for contingencies" by Niemimaa et al. ()

In this article, the authors have focused on Business Continuity (BC) of business models because they have a central role in companies' business strategies and ensure continuity in businesses' revenue streams. They propose that the business model is a crucial part of the BC concept. It should not be considered an espoused business model, but as an actual business model that the organizations implement through the various resources available, as illustrated in figure 1 below.

Figure 1: Strategic BC management framework (Adapted from Niemimaa et al., 2019, p.211)

The value creation part of the approach focuses on the evaluation of contingencies that are a threat to the existing business model and modification of the existing model based on analysis. The value preservation part of the model is concerned with traditional approaches on BC, these approaches can also create value, therefore, the overlap. Value preservation can therefore be viewed as strategic. Social platforms that various technological changes are a serious threat to BC of a company.

The threat is due to a changing operational environment, which is characterized by the Internet of things, crowdsourcing, sharing economy, and big data. While online oriented business models thrive in this environment, the traditional business models are under threat. To secure these threatened businesses, the authors propose Strategic Business Continuity Management, which consists of 1) sustenance of the company business model through value preservation, and 2) evaluation and modification of business model through value creation. Online businesses benefit from insights from the online environment, especially big data, and for the traditional business, it is vital to adapt to as well as adopt some of these benefits (value preservation) and seeks ways to use the strategies offered by online business models (value creation).

Review of "Determinants shaping willingness towards online recycling behavior: An empirical study of household e-waste recycling in China" by Wang et al. (2019)

In this article, Wang et al. (2019) discuss online recycling as a new concept in the age of technology and consider how economic income and education levels affect consumer recycling behavior and its functional path. The theory of planned behavior is used in this research, and the authors hypothesize that; H1, attitudes significantly positively affect willingness to participate in online recycling, H2, subjective norms significantly positively affect willingness to participate in online recycling, and H3, perceived behavior significantly positively control willingness to participate in the recycling of e-waste.

Economic income and education are considered inflicting factors, and thus, the authors hypothesize that; H4, economic motivation positively influences participation in online recycling, H5, oncome level significantly affects positive participation in online recycling, and H6, level of education significantly positively affects participation in online recycling. Economic benefits and sensitivity are also mediating factors. Thus, the hypothesis; H7, income level, and income incentives affect participation in online recycling, and H8, level of education and effects of subjective norms affect participation in online recycling.

A quantitative research design using a questionnaire survey was used as the methodology. A sample of 1225 respondents from the China Sustainable Consumption Survey was used for data collection. Data were analyzed through linear regression. Results showed that perceived behavior control, subjective norms, attitudes, and economic motivation, income, and education level significantly positively affect e-waste online recycling participation. Based on these findings, hypotheses 1-7 are supported, but H8 is not. Based on these findings, it is concluded that residents' income level significantly negatively influences e-waste online recycling platforms. The moderating effect of level of education is insignificant.

Review of "The evolution of platform business models: Exploring competitive battles in...

…are likely to withdraw from foreign markets than those with cross-country network externalities. It is important for managers of platform business models to factor in the geographical scope of network externalities.

Review of "Reducing food waste through digital platforms: a quantification of cross-side network effects" by Mullick and colleagues (2020)

This article examines how to retail store activity on the digital platform used to fight goof waste affects consumer activity, and vice versa, which is also referred to as cross-side network effects. A case study methodology has been used. The case study firm is based in Europe and became operational in 2016 to reduce food waste. Data collected pertains to retail store behavior and consumer behavior. Data was collected from 48 grocery stores who uploaded 159.040 products in their first year on the platform and were viewed by 9985 consumers.

Measurement of retail activity involved calculating last-minute discounts offered on distinct products, and consumer activity was measured by the number of consumers who viewed those distinct products. Analysis of the data was done through the vector autoregressive (VAR) model. Because of panel data, the Panel Vector Autoregressive (PVAR) model was used. The results show that the effect of consumer activity on the online retail store activity is stronger and more long-lasting than the effect of the online store activity on consumer activity.

From a theoretical standpoint, these findings suggest the online retail platforms can effectively create ties between retail stores and consumers in that consumer-to-retail store and retail store to consumer effects are not only prevailing but also asymmetric. From a managerial standpoint, these findings mean that any platform leaders' interventions should be on the consumer side of the market. This article helps to understand online platforms' performance by pointing to the fact that, for e-commerce platforms, any performance influencing initiatives should be aimed towards…

Sources used in this document:

References

Mullick, S., Raassens, N., Haans, H., & Nijssen, E. J. (2020). Reducing food waste through digital platforms: a quantification of cross-side network effects. Industrial Marketing Management. 1-12Niemimaa, M., Järveläinen, J., Heikkilä, M., & Heikkilä, J. (2019). Business continuity of business models: Evaluating the resilience of business models for contingencies. International Journal of Information Management, 49, 208-216.

Stallkamp, M., & Schotter, A. P. (2019). Platforms without borders? The international strategies of digital platform firms. Global Strategy Journal. 1-23Wang, B., Ren, C., Dong, X., Zhang, B., & Wang, Z. (2019). Determinants shaping willingness towards online recycling behavior: An empirical study of household e-waste recycling in China. Resources, Conservation and Recycling, 143, 218-225.

Xiao, Q. (2016). Managing e-commerce platform quality and its performance implication: A multiple-group structural model comparison. Journal of Internet Commerce, 15(2), 142-162.

Zhao, Y., Von Delft, S., Morgan-Thomas, A., & Buck, T. (2020). The evolution of platform business models: Exploring competitive battles in the world of platforms. Long Range Planning, 53(4), 101892.

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