Australia's highly concentrated food retail environment is examined in the context of competitive entry in a small city. Based on a conceptual framework that draws on existing literature, food stores' customers' share of wallet (SOW) is measured in a survey (n=379) which brackets the opening of a new supermarket. A number of variables are recorded in the survey that are not available from other data collection methods. The drivers of SOW are determined using a 2-limit Tobit model which incorporates the direct and interactive aspects of the pathways identified in the Conceptual Framework. At one of the stores (Woolworths), the influence of loyalty schemes is found to vary with customers' perceptions of stores, with implications for enhanced customer targeting by food retail managers. The impact of loyalty programs is found to be mitigated by the entry of a competitor, particularly in the case of price-conscious customers. Senior citizens are found to allocate higher SOW to small rather than large stores, and there are small effects due to the sex of the customer. There are few indications of a bespoke small city model of the drivers of SOW, but a number of interactions are identified for future research.

Empirical studies of customers' response to their favored brands' being out of stock (OOS) have focused on customers' characteristics and have been almost exclusively conducted in metropolitan areas of Europe and North America. Less is known about the effect of new retail market entry on customers' OOS response and the associated implications for retailers and manufacturers in the context of small regional centers and cities. This paper investigates customers' response to OOS in the context of a small Australian city experiencing market entry by a new supermarket. A Multinomial Logit model is used to analyze the primary survey data from 378 food shoppers. Prices for a selection of food items were also tracked for the relevant period. Our results show that changing competitive environment is likely to be a driver of customers’ switching store in response to OOS. Overall, most of the influential variables are positively associated with switching stores rather than switching brands, and this indicates that OOS is more costly for retailers than for manufacturers.

This paper investigates whether different measures of ex-post poverty and ex-ante vulnerability to poverty provide consistent estimates of poverty and vulnerability to poverty across households. Moreover, if there is some heterogeneity in the identification of households as poor and vulnerable, it investigates the degree of mismatch between measures? The ex-post monetary poverty (MP) and multidimensional poverty (MDP) measures are used to identify poor households. Likewise, the ex-ante vulnerability to monetary poverty (VMP) and vulnerability to multidimensional poverty (VMDP) measures are used to identify vulnerable households. Using a large household survey data-set of about 90,000 households from the Punjab province of Pakistan, we find that most of the vulnerable households are accurately identified by the ex-ante measures of vulnerability to poverty. However, the ex-post measures of poverty identify different households as poor. Our results show that 18 percent households experiencing MDP are not captured by the one-dimensional measure of MP. The important implication of this study is that the choice of measures does matter in ex-post poverty identification, but not as much in the identification of ex-ante vulnerability to poverty.

Empirical studies in different developing countries have investigated the impact of social protection (SP) on ex-post poverty; however, few studies analysed the impact of SP on ex-ante vulnerability to poverty (VtP). This paper contributes to the literature by evaluating the impact of SP on vulnerability to poverty (VtP) and poverty rates among households in the Punjab province of Pakistan. A hierarchical modelling approach is used to analyse the Multiple Indicator Cluster Survey (MICS-2011) data of about 90,000 households. Matching methods and simultaneous endogenous switching regression are used to control for potential selection bias and estimate average treatment effects. Our results show that SP has a positive impact in reducing household poverty and VtP, but this impact is mainly driven by a short-term flood relief cash transfer programme, pension of government employees and households’ regular purchase from utility store network.