What the subsistence marketplaces stream is really about: Beginning with micro-level understanding and being bottom-up

This commentary reiterates the essence of the subsistence marketplaces stream in light of the focal paper. The subsistence marketplaces stream provides a granular, micro-level understanding of the intersection of poverty and marketplaces. The term ‘subsistence marketplaces’ was deliberately coined to keep the focus on preexisting marketplaces to learn from in order to design solutions for all contexts. Such marketplaces should be studied in their own right, and not as a means to a preconceived end, whether it be for outside companies or government policy and so forth. We study subsistence marketplaces inside-out rather than outside-in – beginning at the micro level and being bottom-up in deriving implications for many sectors of society. We traverse a journey which is in the opposite direction to beginning with ideological lenses, wherein we have developed an ecosystem of research, forums, curricular innovations and community outreach.     

Response pattern analysis: Assuring data integrity in extreme research settings

Research summary : Strategy scholars increasingly conduct research in nontraditional contexts. Such efforts often require the assistance of third‐party intermediaries who understand local culture, norms, and language. This reliance on intermediation in primary or secondary data collection can elicit agency breakdowns that call into question the reliability, analyzability, and interpretability of responses. Herein, we investigate the causes and consequences of intermediary bias in the form of faked data and we offer Response Pattern Analysis as a statistical solution for identifying and removing such problematic data. By explicating the effect, illustrating how we detected it, and performing a controlled field experiment in a developing country to test the effectiveness of our methodological solution, we encourage researchers to continue to seek data and build theory from unique and understudied settings. Managerial summary : Any form of survey research contains the risk of interviewers faking data. This risk is particularly difficult to mitigate in Base‐of‐Pyramid or developing country contexts where researchers have to rely on intermediaries and forms of control are limited. We provide a statistical technique to identify a faking interviewer's ex post data collection, and remove the associated data prior to analysis. Using a field experiment where we instruct interviewers to fake the data, we demonstrate that the algorithm we employ achieves a 90 percent accuracy in terms of differentiating faking from nonfaking interviewers. Copyright © 2016 John Wiley & Sons, Ltd.     

Understanding the quality–quantity conundrum of customer referral programs: effects of contribution margin,extraversion, and opinion leadership

Firms can substantially profit from customer referrals, but they must understand the different stages of the referral process to determine what drives the number of referrals (first stage), conversion (second stage), and average contribution margin per referral (third stage). Applying a framework that integrates perceptual and behavioral drivers, this study uses a financial services company’s customer survey and transaction data to investigate how the effect of contribution margins of referring customers at all three stages depends on their perceived extraversion and opinion leadership. Extreme extraversion and opinion leadership diminish the positive effect of the contribution margins of referring customers on the number of referrals; their effect on the number of successful referrals is insignificant. In terms of the contribution margin of successful referrals, extraversion has a negative and opinion leadership a positive moderating effect.     

Dynamic risk management

Both financing and risk management involve promises to pay that need to be collateralized, resulting in a financing versus risk management trade-off. We study this trade-off in a dynamic model of commodity price risk management and show that risk management is limited and that more financially constrained firms hedge less or not at all. We show that these predictions are consistent with the evidence using panel data for fuel price risk management by airlines. More constrained airlines hedge less both in the cross section and within airlines over time. Risk management drops substantially as airlines approach distress and recovers only slowly after airlines enter distress.     

Structural breaks in consumption patterns: India 1952-1991

This study improves upon the econometric modelling for testing and incorporating structural breaks for a study on Indian consumption patterns covering a period of four decades and also explores the causes of such breaks. The tests for structural breaks in consumption patterns indicate multiple break points which are not uniform across the population groups and also across commodity groups. Further, the results indicate for the first time, that the breaks could often be induced by the changes in the data collection methodology of the survey and not due to changes in consumer behaviour alone. Apart from this, there is a shift in the consumption pattern during the mid-1980s in both the rural and the urban sectors. For the lowest expenditure class the shift is away from food items with the rural sector showing a change in the price response and the urban sector showing a change in the total expenditure coefficient. For the middle and the upper expenditure classes the shifts are not only from the food items towards non-food items but also from the 'food' group that includes items like cereals, milk and milk products towards the 'other food' group which includes items like vegetables and fruits. Its causes are found to be changes in preferences as well as the income effect.     

Modelling the domestic and foreign tourist arrivals to Tamil Nadu (India)

In recent years, due to the Indian Federal Government's and Tamil Nadu State Government's various initiatives and promotional activities, foreign and domestic tourist arrivals in Tamil Nadu are on the increase. This article aims to model the monthly tourist arrivals (foreign as well as domestic) in Tamil Nadu for monthly time series data during the period 1998 to 2002 using univariate time-series models. As both time series show strong seasonal patterns, we also investigate the possibility of seasonal unit roots in the domestic and foreign tourist arrivals series. The results show that significant growth in domestic and foreign arrivals takes place during the months December to January. Growth rate for domestic tourist arrivals is positive during April and May, but is negative for the foreign tourist arrivals during April and insignificant during May. Such information would be very useful to the Tamil Nadu government and the tourism industry in maximizing the usage of available tourist spot infrastructure and to provide high quality service.     

The effect of public information and competition on trading volume and price volatility

In a one-period model of market making with many exogenouslyinformed traders, we first show that the variance of pricesand expected trading volume depend on the public informationreleased at the start of trading. This is accomplished by representingbeliefs with elliptically contoured distributions, for whichthe form of optimal decision rules does not depend on the specificdistribution used. Second, if the model is altered so that thedecision to become informed is made endogenous, then the decisionrules of the market-maker and informed traders depend on thepublic information. Third, in a multiperiod model with manyinformed traders and long-lived private information, recursionformulas similar to those of Kyle (1985) hold for all ellipticallycontoured distributions, trading volume is autocorrelated and,unless per period liquidity trading is bounded away from zeroas new trading periods are added, informed traders' profitsvanish.     

Implementation of Social Innovations in Subsistence Marketplaces: A Facilitated Institutional Change Process Model

Implementation of social innovations in subsistence marketplaces often fails as a result of not bringing about institutional change. In this article, we study the process through which social enterprises facilitate local communities in effecting the process of institutional change as they introduce social innovations. Analyzing rich ethnographic data from 19 social enterprises, we develop the process of “facilitated institutional work” for implementing social innovation. We present a process model for implementing social innovation with four distinct stages involving social enterprises—(1) legitimating themselves within local communities, (2) disrupting aspects of the local institutional environment, (3) helping re‐envision institutional norms or practices, and (4) resourcing the institutional change process. The four stages relate to important concerns that local communities have in working with social enterprises implementing social innovations. These community‐level concerns revolve around the following questions: (1) Why should we allow an external social enterprise to be involved in our affairs? (2) Why do we need to change? (3) What should we change and what should we sustain? and (4) What role should we play in implementing change (such as in mobilizing resources)? This article demonstrates that bringing about institutional change is often necessary for implementing social innovations in subsistence marketplaces. The findings depict a participatory approach in which social enterprises work with local communities to bring about the institutional conditions necessary for implementing social innovation.     

Distribution and drivers of costs in type 2 diabetes mellitus treated with oral hypoglycemic agents: a retrospective claims data analysis

Objective:

To describe the distribution of costs and to identify the drivers of high costs among adult patients with type 2 diabetes mellitus (T2DM) receiving oral hypoglycemic agents.

Methods:

T2DM patients using oral hypoglycemic agents and having HbA1c test data were identified from the Truven MarketScan databases of Commercial and Medicare Supplemental insurance claims (2004–2010). All-cause and diabetes-related annual direct healthcare costs were measured and reported by cost components. The 25% most costly patients in the study sample were defined as high-cost patients. Drivers of high costs were identified in multivariate logistic regressions.

Results:

Total 1-year all-cause costs for the 4104 study patients were $55,599,311 (mean cost per patient?=?$13,548). Diabetes-related costs accounted for 33.8% of all-cause costs (mean cost per patient?=?$4583). Medical service costs accounted for the majority of all-cause and diabetes-related total costs (63.7% and 59.5%, respectively), with a minority of patients incurring >80% of these costs (23.5% and 14.7%, respectively). Within the medical claims, inpatient admission for diabetes-complications was the strongest cost driver for both all-cause (OR?=?13.5, 95% CI?=?8.1–23.6) and diabetes-related costs (OR?=?9.7, 95% CI?=?6.3–15.1), with macrovascular complications accounting for most inpatient admissions. Other cost drivers included heavier hypoglycemic agent use, diabetes complications, and chronic diseases.

Limitations:

The study reports a conservative estimate for the relative share of diabetes-related costs relative to total cost. The findings of this study apply mainly to T2DM patients under 65 years of age.

Conclusions:

Among the T2DM patients receiving oral hypoglycemic agents, 23.5% of patients incurred 80% of the all-cause healthcare costs, with these costs being driven by inpatient admissions, complications of diabetes, and chronic diseases. Interventions targeting inpatient admissions and/or complications of diabetes may contribute to the decrease of the diabetes economic burden.     

Consumer-driven media planning and buying

Media planning and buying has historically focused on efficient message distribution. Thus, most media planning approaches have focused on optimization models based on estimated reach and frequency. Those models assumed a hierarchy of effects base where consumers move through a purchasing journey driven by assumed media exposures. In this exploratory paper, an argument is made for a consumer-generated media consumption model. Thus, their focus is on media influence rather than simply exposures. The model is demonstrated with data from a US-based online consumer data-set. The authors posit technology has made their approach superior to traditional models. A set of managerial implications is included.