Search results

The purpose of this paper is to add to the small but growing body of research examining the influence of founder gender on new venture access to venture development programs.

Hypotheses were tested utilizing a sample of 482 nascent technology ventures which applied for admittance into a venture development organization headquartered in the southern region of the United States from March 2004 through February 2016.

Findings suggest that female-founded applicant ventures experience a higher likelihood of acceptance into venture development programs than male-founded applicant ventures. Results further suggest that social attention to gender equality reduces this effect for female-founded applicant ventures. Findings extend the understanding of the gendered nature of high-technology venturing and venture development organizations.

The findings of this study may not generalize to new ventures operating in other contexts (e.g., non-U.S., low-tech, and other venture development programs). Additionally, this study's design and data limitations do not allow for the establishment of causality or address founder motivations to apply for acceptance into venture development programs.

This study adds to empirical findings regarding the influence of founder gender on new venture acceptance into venture development programs by developing and testing competing hypotheses. This study also extends extant research by examining the moderating effect of social attention to gender equality on the hypothesized relationships between founder gender and acceptance into venture development programs.

The purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.

Using individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).

The results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.

Substantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.

This paper tests whether Bayesian A/B testing yields better decisions that traditional Neyman-Pearson hypothesis testing. It proposes a model and tests it using a large, multiyear Google Analytics (GA) dataset.

This paper is an empirical study. Competing A/B testing models were used to analyze a large, multiyear dataset of GA dataset for a firm that relies entirely on their website and online transactions for customer engagement and sales.

Bayesian A/B tests of the data not only yielded a clear delineation of the timing and impact of the intellectual property fraud, but calculated the loss of sales dollars, traffic and time on the firm’s website, with precise confidence limits. Frequentist A/B testing identified fraud in bounce rate at 5% significance, and bounces at 10% significance, but was unable to ascertain fraud at the standard significance cutoffs for scientific studies.

None within the scope of the research plan.

Bayesian A/B tests of the data not only yielded a clear delineation of the timing and impact of the IP fraud, but calculated the loss of sales dollars, traffic and time on the firm’s website, with precise confidence limits.

Bayesian A/B testing can derive economically meaningful statistics, whereas frequentist A/B testing only provide p-value’s whose meaning may be hard to grasp, and where misuse is widespread and has been a major topic in metascience. While misuse of p-values in scholarly articles may simply be grist for academic debate, the uncertainty surrounding the meaning of p-values in business analytics actually can cost firms money.

There is very little empirical research in e-commerce that uses Bayesian A/B testing. Almost all corporate testing is done via frequentist Neyman-Pearson methods.

Statistics show that the construction sector has the second-highest number of accident cases in Malaysia. A total of 100, 000 construction workers suffer from work-related bad health each year. Scaffolding accidents are the second cause of accidents on construction sites. Therefore, this present research provided answers to the following questions: (1) what are the causes of scaffolding accidents and (2) what are the possible measures to reduce scaffolding accidents?

The research developed a questionnaire instrument that included 24 causes of scaffolding accidents and 21 remedial actions. The research was based on a cross-sectional survey questionnaire administered to 129 members of construction organizations.

Data revealed that scaffolding-related cases caused a total of 70% of the deaths/injuries on sites. Furthermore, scaffolding accidents were mainly caused by a lack of guard rails on scaffoldings, poor inspections, improper assembly, a poor safety culture, poor attitudes towards safety, poor footing of scaffoldings and unsecured planking. To reduce scaffolding accidents, there must be a lifeline on scaffolding, proper guardrails and proper assembling of scaffoldings, and preventing access to incomplete or defective scaffoldings. The 24 causes are structured into six factors through factor analysis and the 21 remedial actions into six factors.

This research serves as the first attempt to conduct broad research on the causes and remedial actions concerning scaffolding accidents on construction sites in Malaysia. Theoretically, the research has provided fresh insights into the impact of scaffolding accidents.

With the context of changing global and local populations and, for example, their composition and distribution, this paper offers insight to food shopping in later life with a focus on Nottingham and Nottinghamshire in the East Midlands. The work is relevant and important due to the specific population makeup of this area and the challenges in achieving the UN Sustainable Development Goals (SDGs) as a result of population changes/challenges.

The work takes an interdisciplinary view and draws on literature from both social policy and social care and business and marketing. Using this work as a grounding, and insights to primary research from a wider study in this area, the paper offers discussion and comment on:

• the importance of food and food shopping in later life;

• issues of, and concerns for, health, well-being, identity and community maintenance and resilience (as a direct result of the challenge to SDG achievement); and

• the role(s) and responsibility of business from a core business and wider business/corporate responsibility perspective as a reflection of the above and findings of the work.

the importance of food and food shopping in later life;

issues of, and concerns for, health, well-being, identity and community maintenance and resilience (as a direct result of the challenge to SDG achievement); and

the role(s) and responsibility of business from a core business and wider business/corporate responsibility perspective as a reflection of the above and findings of the work.

Using primary research undertaken by the authors, the paper supports findings from existing work from across social policy and care and business and management – related to the practicalities, challenges and the role of and approaches to food shopping in later life. It specifically offers insight to the efforts made by older food shoppers to maintain their independence and support their choices in a context of interdependence (e.g. within a family, community and environment). The importance social aspects of food shopping (as a counter to isolation and loneliness for example) are also identified and how, for example, the actions of business(es) may undermine the efforts (and resilience) of individuals and communities. “Better” understanding of food shoppers by business and other stakeholders is promoted.

This article advances a conceptual typology delineating the differences and similarities between business- and social-sector new venture creators. Our classification scheme differentiates business and social entrepreneurs, considering characteristics of social entrepreneurs in a larger entrepreneurial context.Within a conceptual 2x2 typology based on two dimensions: drive (passion vs. business) and desired return (financial ROI vs. social ROI), we identify and classify 80 examples of new venture creators into one of the quadrants of an enterprise model of entrepreneurs. Preliminary results reveal similarities between social and traditional entrepreneurs and differentiate social entrepreneurs in terms of traits, goals, tendencies, and motivational sources.

The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution.

The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments.

Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes.

The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept.

The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

The purpose of this paper is to promote decision-making structures between the customer and the supplier in a highly uncertain environment. This phenomenon of demand-supply chain synchronisation includes sharing of high-quality and timely demand and supply information in order to improve the quality and speed of decision-making.

The study was carried out as an abductive case study, which started from empirical observations that did not match the prior theoretical framework. Through abductive reasoning and empirical experiments, the prior framework was extended to a new synchronisation model and tools that better accommodate the observed need.

A new co-innovation toolbox was developed to create common understanding of demand-supply chain synchronisation between the customer and the supplier. The toolbox includes Demand Visibility Point-Demand Penetration Point, Supply Visibility Point–Supply Penetration Point and Integrative Synchronisation tools.

The study extends the current models and tools of demand-supply chain synchronisation. With the new toolbox, the development needs of decision-making structures can be identified more comprehensively than with the current tools.

The developed visual toolbox helps partners create a common understanding of problems and development possibilities in demand-supply chain synchronisation in a highly uncertain environment. Common understanding is a starting point for changing decision-making structures to improve the overall performance of a demand-supply chain.

The new toolbox is both more comprehensive and more detailed than the previous tools.

In this paper, the authors argue that the blueprint that was organically developed over the course of approximately three centuries, from The Grand Tour to this day, is likely to see something close to a repeat in the development of that final frontier.

The study used the methodology of reviewing the literature and model comparison.

Opportunities will expand and change along the same trends that lead The Grand Tour to evolve into mass tourism, because as in the past people's perceptions about what is possible and reasonable will change the more common such once fictional ideas become reality.

Nothing is in the current tourism literature, on this topic. This is new and unique.