Abstract

Keywords

1. Introduction

2. Theoretical Background

3. Materials and Methods

4. Results

5. Discussion and Conclusions

6. Limitations and suggestions for future research

CRediT authorship contribution statement

Appendix A. Semi-structured interview guide (Ang et al., 2000; Baytiyeh, 2018; Kennett-Hensel et al., 2012; Priporas et al., 2017)

Appendix B

Appendix C

Appendix D

Appendix E

References

Vitae

Abstract

This study seeks to unravel the factors that have triggered changes in individuals’ engagement with online consumption during the COVID-19 crisis and investigate the influence of digital technologies on the retail ecosystem during the lockdowns, as seen through the eyes of consumers. In doing so, a qualitative empirical research approach was adopted, and data was collected via in-depth interviews with 35 respondents during the COVID-19 lockdown in China. The study has delineated a systematic mapping of the retail ecosystem’s reactions to the COVID-19 shock. Three overarching dimensions related to consumers’ online purchasing behaviors during the COVID-19 pandemic were identified: triggers of enhanced digital engagement, transformative capacity of digital technologies, and socio-economic adaptability during crises. The relevant themes underlying each aggregate dimension were further elaborated with evidence from the interviews. The study findings advance the extant literature on purchasing behavior and online retailing in times of crisis and offer important practical implications on improving crisis management capabilities of the retail ecosystem via digital technologies. As a final output, four propositions were extracted to serve for further research.

1. Introduction

In the last three decades, the technological developments of Web 2.0 and Web 3.0 have largely served as the driving forces for the Marketing 3.0 era of customization, and the digitalization age of Marketing 4.0, respectively (Erragcha & Romdhane, 2014; Shan et al., 2020). Information and communication technologies (ICTs), online marketing platforms and sophisticated digital devices have advanced exponentially, supporting the growth of various economic sectors (Zhu, 2021). Specifically, in the retail sector, various digital technologies support multichannel strategies or even an omni-channel approach, which offer consumers a range of alternatives in purchasing goods and services (Jin & Shin, 2020). Mobile devices, mobile apps, augmented reality and virtual reality applications, and various types of bots have already been in service instead of or combined with traditional human-to-human interactions – in either physical, online or hybrid offline/online settings – to serve customers’ needs and retailers’ goals (Hu & Tracogna, 2020; Verhoef et al., 2015).

The digital transformation of the retail sector has emerged through the natural evolution of digital technologies’ implementation, so retail organizations and individuals would facilitate their access to world markets, offering improved serviceability, and building competitive advantages (Altintas¸ et al., 2020). This set of retail actors comprise a generic retail ecosystem, who interchange goods and services for money and data, contributing to economic value streams. These actors can be branch retailers, online retailers, multi-channel retailers, IT-solution providers, service providers, store equipment providers, producers, data suppliers, logistics firms, and consumers (Bottcher et al., 2021 ¨ ).

Conservation organizations increasingly target ecosystem services alongside biodiversity, yet it remains unclear whether ecosystem service goals reinforce or detract from those for biodiversity. We assess tradeoffs between biodiversity and ecosystem services and test the hypothesis that the severity of this tradeoff is a function the breadth of taxa and ecosystem services targeted. We identify optimal conserved lands networks for four taxa, four ecosystem services, and all possible combinations of each. We then assess the amount of biodiversity and ecosystem service contained within each network, its conservation cost, and its overlap with every other network. We find that overlap varies widely across individual ecosystem services and taxa, and that networks targeting multiple services contain more biodiversity than networks targeting a single service. Safeguarding a given amount of ecosystem service and biodiversity through joint optimization requires a 13% increase in conservation budgets relative to achieving targets for biodiversity alone, and results in a 22% budget savings relative to achieving targets for each though separate efforts. We conclude that including ecosystem services goals alongside those for biodiversity is likely have a net positive impact on biodiversity, especially when a broad suite of services are targeted.

Introduction

Supporting the wellbeing of a growing human population while avoiding biodiversity loss is a central challenge of sustainable development (ICSU, 2015; Millennium Ecosystem Assessment, 2005; Steffen et al., 2015). Ecosystem services (ES) are the benefits that people derive from nature (Daily, 1997; Millennium Ecosystem Assessment, 2005). Development-driven environmental degradation is rapidly eroding both biodiversity (Butchart et al., 2010; Ceballos et al., 2015; Newbold et al., 2015; Pimm et al., 2014) and those ecosystem services whose value is not captured in markets (Foley et al., 2005; Millennium Ecosystem Assessment, 2005; Sutton et al., 2016). By making explicit the link between the well-being of people and nature, ES have the potential to serve as common ground for human development and conservation (Millennium Ecosystem Assessment, 2005). As a result, conservation organizations and governments are increasingly prioritizing ecosystem services (Bateman et al., 2013; Donovan et al., 2015; Guerry et al., 2015; Ruckelshaus et al., 2013). How will an ES focus impact biodiversity? Considerable debate has arisen among the conservation community over whether an ES approach is undercutting or bolstering traditional biodiversity goals (McCauley, 2006; Reyers et al., 2012). On the one hand, the resources once allocated specifically to protecting nature for its own sake are now being used to protect the parts of nature that have the highest utility to people.

Land is one of the most important and limited resources and provides a range of essential ecosystem services (ES) for human well-being (Fürst et al., 2013). However, increasing human demands for natural resources, cultivable lands, and a variety of ES along with intensive changes to biogeophysical structures and processes might negatively impact the development of societies (Mooney et al., 2009; Sonter et al., 2017). In this context, land management and policy decision-making are recognized as the most important drivers for these impacts and the subsequent losses in the ES supply at multiple scales (Schosser et al., 2010; Verburg et al., 2015). Spatial planning is a key instrument for decision-making in terms of coordinating human activities and their influences on land systems, and subsequently on the quality, quantity and spatial distribution of ES (Geneletti 2011, 2013; Mascarenhas et al., 2015). Including ES in spatial planning is considered to be a suitable approach for informing, communicating and facilitating consensus building among different actors because it provides a basis for multisectoral and interdisciplinary collaboration (Albert et al., 2014; Galler et al., 2016). An essential aspect in the integration of ES in spatial planning is the issue of scale and the multiple levels of decision-making involved. Supply and demand of ES, as well as their interrelations, vary from local to regional and global scales, which at the same time affect a wide range of stakeholders (Geijzendorffer and Roche, 2014; Hein et al., 2006). Thus, spatial planning has the potential to mainstream ES across multiple governance levels, since it provides an umbrella for coordinating different policy instruments in a more strategic manner (Greiber and Schiele, 2011). As discussed by Geneletti (2011) and Mascarenhas et al. (2014), the integration of ES into spatial planning should consider existing instruments, such as strategic environmental assessment (SEA).

مقاله سال 2016

The term ‘innovation ecosystems’ has become popular in industry, academia, and government. It is used in corporate, national, or regional contexts, in idiosyncratic ways. It implies a faulty analogy to natural ecosystems, and is therefore a poor basis for the needed multi-disciplinary research and policies addressing emerging concepts of innovation.

Frenkel and Maital (2014) find an early use of “innovation ecosystem” in a New York Times op-ed by William Kennard, a former Chairman of the US Federal Communications Commission. Other earlier comparisons of business environments to ecological systems include Carroll (1988), Hannan and Freeman (1989), Moore (1993), and Schot (1998). (All owe intellectual debt to Nelson and Winter (1982), though the latter’s work on evolution of technology did not imply there is an ecology of innovation.) However, these researchers may not have been aware that other social scientists had already left the questionable ecosystem analogy behind; see especially Haynes (1971).

Jackson (2011) defines an innovation ecosystem as “the complex relationships that are formed between actors or entities whose functional goal is to enable technology development and innovation.” (A supplementary file, giving more background on innovation systems and their relation to technology-based economic development, accompanies this article.) He continues, The actors include the material resources (funds, equipment, facilities, etc.) and the human capital (students, faculty, staff, industry researchers, industry representatives, etc.) that make up the institutional entities participating in the ecosystem (e.g. the universities, colleges of engineering, business schools, business firms, venture capitalists, industry-university research institutes, federal or industrial supported centers of excellence, and state and/or local economic development and business assistance organizations, funding agencies, policy makers, etc.). The innovation ecosystem comprises two distinct, but largely separated economies, the research economy, which is driven by fundamental research, and the commercial economy, which is driven by the marketplace.