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Recent findings by Hamilton (Journal of Political Economy, 2000) suggest that the self-employed do not receive a monetary premium for the risk and uncertainty associated with business ownership. The purpose of this paper is to show that income underreporting by entrepreneurs can explain the lack of evidence for monetary premia. Using a large national data set (Panel Study of Income Dynamics (PSID)), the author first document evidences of underreporting, and then proceed to make alternative comparisons using measures of consumption. The author finds that the self-employed enjoy large earnings premia that are reflected in their consumption.

Using PSID the author creates and analyzes a household level data set comparing monetary rewards of self-employment to those of wage work. The author employs previous findings about entrepreneurial saving behavior to show, via quintile regression analysis, consumption rewards to entrepreneurship, and compare those rewards to income rewards.

The author finds self-employed enjoying significant consumption premia, over the income premia, throughout the income distribution. Contrary to previous claims (e.g. see Hamilton, 2000) the author finds that self-employment is a financially rewarding undertaking. Due to different income reporting metrics and tax exemption structure entrepreneurs enjoy even larger monetary rewards when compared to wage workers along consumption axis. In light of these findings the paper proposes consumption, rather than income metrics, to be applied when quantifying rewards to self-employment.

Household level of analysis is a major drawback in using this approach. This is an outcome of consumption data collected and reported on household rather than individual income. Because of this limitation transitions into and out of self-employment cannot be separated from household changes, i.e., divorces and marriages. However, divorces and marriages are assumed to not have systematic component favoring wage workers or self-employed.

Significant resources are allocated toward supporting entrepreneur. Small business administration, congress, state agencies, and community development corporations contentiously outline both risks associated with failure rates and low rewards to self-employment. This paper provides policymakers with better tools for assessment of true monetary rewards. Better assessment of true rewards, especially contrasting corporations vs individual earnings in self-employment should enable the policymakers to provide better support for the entrepreneur.

Entrepreneur, in social light, is perceived as a much more successful individual. This view differs with recent data. Previously overly naive positive estimate of entrepreneur has been attributed to the bias of survival. This paper provides additional support for social view of entrepreneur by pointing to an overlooked, by the policymakers and most researchers, information segment – consumption data. These additional benefits that have been well understood by the public can now be substantiated for the policymakers.

This paper develops unique method for documenting monetary rewards to entrepreneurship. Using information about entrepreneurial saving behavior this paper demonstrates significant monetary premia, over reported income premia enjoyed by entrepreneurs. The premia is documented throughout income distribution and is not an outcome of entrepreneurial superstars or even average entrepreneur.

The purpose of this paper is to introduce a new methodology called overall greenness performance for value stream mapping (OGP-VSM). Using value-added concepts, this approach has the potential to integrate, measure, control and improve productive and environmental performance in accordance with a company’s context.

The OGP-VSM approach was developed by reviewing and integrating the environmental aspects of existing lean thinking tools and approaches.

This research revealed the lack of practical integration between productive and environmental performance. Using OGP-VSM, managers can see that environmental practices have a direct impact on productivity. OGP-VSM allows a balance to be found between lean and green practices in order to achieve the simultaneous improvement of productivity and environmental performance.

The proposed approach is applied to a case study in an automotive company in Spain and lays the groundwork for moving toward functional environmental sustainability in manufacturers.

Companies are increasingly implementing environmentally focused practices. Pursuing environmentally friendly (green) performance poses several challenges, but it also affords opportunities to create new methodologies for generating a competitive advantage for manufacturing companies. There are a limited number of approaches to drawing together the elements and attributes that are essential for a holistic, practical and long-lasting improvement of environmental performance in the manufacturing sector.

Since the publication of Van Raaij and Verhallen’s seminal work in European Journal of Marketing in 1994, identifying the domain-specific market segmentation approach as one of the most feasible for segmenting markets, there has been surprisingly limited development in this field, with the food domain as the only exception. This study aims to develop a methodological approach using latent class mixture modelling as contribution in the domain-specific market segmentation field.

This study captures the AIO lifestyle perspective using a domain-specific 80-item algorithm which has the wine (product) domain as its focus. A sample size of 811 consumers is used from data collected by means of the CATI approach.

The authors use four criteria for model selection: comparison of the Bayesian information criterion (BIC) statistic, comparison of classification error, verification of the interpretation of the derived segments and, finally, use of the conditional bootstrap procedure to test whether the selected model provides a significant improvement over the previous model. The five-segment model option yields a minimum BIC, the classification error measure is minimal and is easier to interpret than the other models. Segment descriptions for the five identified lifestyle-based segments are developed.

Segmentation by traditional k-means clustering has proven to be less useful than the more innovative alternative of mixture regression modelling; therefore, the authors identify segments in the market on the basis of individuals’ domain-specific lifestyle characteristics using a latent class mixture modelling approach.

Following the attainment of a clear and robust market segmentation structure, the simultaneous analysis of the lifestyles, demographics and behaviours of consumers as nexus of the domain-specific segmentation approach, provides rich and valid information accurately informing the market segment descriptions.

The authors make a substantive contribution by developing a methodological approach using latent class mixture modelling; the first of its kind in the area of domain-specific segmentation. Next, they use the discriminant and/or predictive validity of the 80-scale items to predict cluster membership using the WRL algorithm. Finally, the authors describe the identified market segments in detail and outline the practical implications.

The purpose of this paper is to establish correlations among the input variables of production within themselves and input variables of consumption within themselves and to forecast the production and consumption of the rice.

The production and consumption of rice crop is governed by diverse variables. In the present study five key input variables for production of rice based on literature review and the authenticated data available from agricultural sources have been selected. These variables are area sown, agricultural workers (AW), area irrigated, growth rate and yield per hectare. On similar basis four key input variables responsible for consumption of rice are considered, namely, price of rice, population, poverty ratio and per capita net national product (NNP).

Correlation analysis showed that priority wise production of rice depends upon yield per hectare, percentage irrigation, AW and area sown. The growth rate is found to be having insignificant correlation with other variables of production and hence was omitted from subsequent study. Correlation analysis also showed that priority wise consumption depends upon whole sale price per ton, population and the per capita NNP. The poverty ratio is found to be having insignificant correlation with other variables of consumption and hence was omitted from subsequent study. The outcomes of the correlation analysis are utilized for designing rule base for fuzzy inference system (FIS) to forecast the production and consumption of the rice. Subsequently Bayesian technique is used to forecast production and consumption and its results are compared with the results of fuzzy inference analysis.

There are many techniques used for forecasting purpose but FIS and Bayesian technique outperform others. In the present study, the authors therefore focussed on these two techniques. Bayesian technique takes into account the expert opinion at the current conditions whereas FIS uses previously designed rule base. Besides discussing the appropriateness of these two techniques for forecasting production and consumption of rice, their forecasting outcomes will help in logistical and operational planning of the resources at national level, farmers’ level and traders’ level.

After working through the case and the assignment questions, students will be able to understand the current practices and importance of influencer marketing strategies within overall marketing strategies; appreciate both the debate and dissonance that surround influencer performance measures; outline the key elements of Qoruz.com’s investments and efforts that brought them success; understand the strategic intent and justify the logic of operationalisation of Qoruz.com by creating two different SBUs after they launched a vastly improved tech platform; and evaluate potential strategies that Qoruz.com could use to move ahead and cement its supremacy in the influencer marketing space.

Interest in influencer marketing which found many takers during the pandemic was expected to intensify and form the core of many brand strategies. Coupled with this heightened interest and increased budget overlay, demands from brands and agencies alike for clearer ROI linkages and KPIs that have better correlation with business goals, have gained momentum. Qoruz, an early entrant in the influencer marketing space in India, attributed their success to their focus on product innovation and service quality. From a predominantly narrow service offering providing analytics that facilitated decision-making for influencer marketing campaigns, their recently launched multi-feature platform enabled them to expand their services and consolidate their position. However, today, in an increasing volatile market, drawn by the high growth trajectory of the influencer marketing space, many players had jumped in and tried to introduce technology-based platforms with almost similar features while aggressively playing the price card. With the monetary and economic conditions under pressure and constantly changing demands of clients, Qoruz.com found itself faced with a dilemma to protect their first mover advantage. The co-founders of Qoruz realised that to give confidence to their loyal client base, and really cement their leadership, they would need to urgently take stock and relook at their strategy afresh relying on their deep experience of the industry, loyalty of their customers and their tech-centric DNA to build a holistic and ambitious strategy.

This case is designed for use by graduate and under-graduate level students in marketing management and strategic management courses.

Teaching notes are available for educators only.

CSS 11: Strategy.

Reducing fuel consumption of unmanned aerial vehicles (UAVs) during transient operation is a cornerstone to achieve environment-friendly operations. The purpose of this paper is to develop a control scheme that improves the fuel economy of a turbojet in its full operating envelope.

A novel direct-thrust linear quadratic integral (LQI) approach, comprised by an optimal observer/controller satisfying specified performance parameters, is presented. The thrust estimator, based in a Wiener model, is validated with the experimental data of a micro-turbojet. Model uncertainty is characterized by analyzing variations between the identified model and measured data. The resulting uncertainty range is used to verify closed-loop stability with the circle criterion. The proposed controller provides stable responses with the specified performance in the whole operating range, even with after considering plant nonlinearities. Finally, the direct-thrust LQI is compared with a standard thrust controller to assess fuel economy and performance.

The direct-thrust LQI approach reduced the fuel consumption by 2.1090% in the most realistic scenario. The controllers were also evaluated using the environmental effect parameter (EEP) and transient-thrust-specific fuel consumption (T-TSFC). These novel metrics are proposed to evaluate the environmental impact during transient-thrust operations. The direct-thrust LQI approach has a more efficient fuel consumption according to these metrics. The results also show that isolating the thrust dynamics within the feedback loop has an important impact in fuel economy. Controllers were also evaluated using the EEP and T-TSFC. These novel metrics are proposed to evaluate the environmental impact during transient-thrust operations. The direct-thrust LQI approach has a more efficient fuel consumption according to these metrics. The results also show that isolating the thrust dynamics within the feedback loop has an important impact in fuel economy.

This study shows the design of an effective direct-thrust control approach that minimizes fuel consumption, ensures stable responses for the full operation range, allows isolating the thrust dynamics when designing the controller and is compatible with classical robustness and performance metrics. Finally, the study shows that a simple controller can reduce the fuel consumption of the turbojet during transient operation in scenarios that approximate realistic operating conditions.

The purpose of this paper is to provide clearer insights into and identify the key consumer behaviour metrics of the lower alcohol category (<11 per cent ABV) in the UK wine market.

Data were collected via an online survey from a sample size of 598 regular UK wine drinkers. To operationalise the study, five research questions were formulated. A highly structured quantitatively directed questionnaire was designed to find the answers to the research questions.

Barriers to a larger uptake of the product category included non-availability of the products, lower quality perceptions, taste issues, lack of awareness, lack of alcohol's “feel effect” and absence of a lower alcohol drinking occasion. Many UK consumers are not yet convinced how/if lower alcohol wine fits into their wine drinking occasions. The lower ABV wine buyer's main profile characteristics are weighted towards females, Millennial and Baby Boomer age generations, mostly mid to low income, who drink mainly white and rosé wines. Lower alcohol on its own is not seen as a big benefit, thus lower ABV wines should be more creatively communicated to sell the benefits.

This study contributes to the knowledge base in that it is the first to investigate consumer behaviour metrics as regards lower ABV wine in one of the world's leading markets, in the process providing some important baseline research information on this category. As such it is of value to academic researchers and practitioners alike.

Virtual machines (VMs) are suggested by the providers of cloud services as the services for the users over the internet. The consolidation of VM is the tactic of the competent and smart utilization of resources from cloud data centers. Placement of a VM is one of the significant issues in cloud computing (CC). Physical machines in a cloud environment are aware of the way of the VM placement (VMP) as the mapping VMs. The basic target of placement of VM issue is to reduce the physical machines' items that are running or the hosts in cloud data centers. The VMP methods have an important role in the CC. However, there is no systematic and complete way to discuss and analyze the algorithms. The purpose of this paper is to present a systematic survey of VMP techniques. Also, the benefits and weaknesses connected with selected VMP techniques have been debated, and the significant issues of these techniques are addressed to develop the more efficient VMP technique for the future.

Because of the importance of VMP in the cloud environments, in this paper, the articles and important mechanisms in this domain have been investigated systematically. The VMP mechanisms have been categorized into two major groups, including static and dynamic mechanisms.

The results have indicated that an appropriate VMP has the capacity to decrease the resource consumption rate, energy consumption and carbon emission rate. VMP approaches in computing environment still need improvements in terms of reducing related overhead, consolidation of the cloud environment to become an extremely on-demand mechanism, balancing the load between physical machines, power consumption and refining performance.

This study aimed to be comprehensive, but there were some limitations. Some perfect work may be eliminated because of applying some filters to choose the original articles. Surveying all the papers on the topic of VMP is impossible, too. Nevertheless, the authors are trying to present a complete survey over the VMP.

The consequences of this research will be valuable for academicians, and it can provide good ideas for future research in this domain. By providing comparative information and analyzing the contemporary developments in this area, this research will directly support academics and working professionals for better knowing the growth in the VMP area.

The gathered information in this paper helps to inform the researchers with the state of the art in the VMP area. Totally, the VMP's principal intention, current challenges, open issues, strategies and mechanisms in cloud systems are summarized by explaining the answers.

The purpose of this study is to understand the effect of price promotions, venue and place of residence on low‐risk, risky and high‐risk alcohol consumption behaviour of young women between 18 and 24 years of age who attend university in Australia, Wales and Germany.

The quantitative, self‐administered questionnaire collected data from a convenience sample of three universities in three OECD countries with high alcohol consumption being: a regional Australian university (n=305), a city Welsh university (n=354) and a rural German university (n=325).

First, the multinomial logistic regression results revealed that price promotions and venue influenced alcohol consumption in Wales alone while place of residence influenced alcohol consumption in Australia; however, price promotions, venue and place of residence had no effect on young women attending university in Germany. Second, the binomial logistic regression results for Wales reported a sensitivity to price promotions for all three alcohol consumption risk classifications; however, location was of little consequence to risky drinkers when compared to high risk drinkers. For Australia, the place of residence did not influence alcohol consumption for both risky and high‐risk drinkers.

The value of this study lies in the examination of three levels of alcohol consumption – low‐risk, risky and high‐risk – for the same cohort across three countries using the same test instrument and standard alcohol consumption metrics. As such, this study provides a more meaningful macro view of alcohol consumption; thus has the capacity to contribute to effectual intervention strategies.

The purpose of this paper is to facilitate a better understanding of the insights provided by adopting a behaviourism perspective of the socio-demographics, consumption dynamics and retail channel patronage of wine consumers and the potential marketing implications these have.

Systematic random sampling yielded 811 surveys of wine consumers collected at households across Australia’s three main consumption metropoles. A hierarchical multiple regression model is used to test the predictive ability of the socio-demographical variables, gender and age, on personal wine consumption.

Specific differences exist in the consumption behaviour and wine type preferences of males and females, and between generational cohorts, specifically Millennial and older consumers. There are gender significant differences in wine type consumption, which in turn is moderated by not only the “classical” socio-demographic variables, but also the retail outlet types preferred for product purchase. Younger Millennial females place more importance on external choice cues in making their buying decision than males. The gender and age generation socio-demographic variables are not strong predictors of personal wine consumption.

Opportunities exist for niche-marketed brands targeted at specific segments such as young females and this study highlighted their specific needs and consumer behaviour dynamics.

This study illustrates through carefully executed wine consumer behaviour research, directed by questioning from the extant literature, how information derived from a behaviourism perspective can intelligently inform marketing strategies. In the process, it also provides “baselines” for future research.