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In the field of behavioral disabilities, systematic direct observation (SDO) has been an integral tool for describing and explaining relationships between student and teacher behavior in authentic classroom settings. However, this method of measurement can be resource-intensive and presents a series of complex decisions for investigators. The purpose of this chapter is to review a series of critical decisions investigators must make when developing SDO protocols to address their research questions. After describing each decision point and its relevance to the measurement system, we identify trends and special considerations in the field of behavioral disabilities with respect to each decision. We organize content according to deciding what to measure, deciding how to measure it, and critical steps to prevent system breakdowns. Finally, we identify avenues for research to further the impact of SDO in the field of behavioral disabilities.

Individuals’ driving behavior data are becoming available widely through Global Positioning System devices and on-board diagnostic systems. The incoming data can be sampled at rates ranging from one Hertz (or even lower) to hundreds of Hertz. Failing to capture substantial changes in vehicle movements over time by “undersampling” can cause loss of information and misinterpretations of the data, but “oversampling” can waste storage and processing resources. The purpose of this study is to empirically explore how micro-driving decisions to maintain speed, accelerate or decelerate, can be best captured, without substantial loss of information.

This study creates a set of indicators to quantify the magnitude of information loss (MIL). Each indicator is calculated as a percentage to index the extent of information loss (EIL) in different situations. An overall information loss index named EIL is created to combine the MIL indicators. Data from a driving simulator study collected at 20 Hertz are analyzed (N = 718,481 data points from 35,924 s of driving tests). The study quantifies the relationship between information loss indicators and sampling rates.

The results show that marginally more information is lost as data are sampled down from 20 to 0.5 Hz, but the relationship is not linear. With four indicators of MILs, the overall EIL is 3.85 per cent for 1-Hz sampling rate driving behavior data. If sampling rates are higher than 2 Hz, all MILs are under 5 per cent for importation loss.

This study contributes by developing a framework for quantifying the relationship between sampling rates, and information loss and depending on the objective of their study, researchers can choose the appropriate sampling rate necessary to get the right amount of accuracy.

This study compares two methods of data collection for students' social behaviors. One method employed time sampling procedures, while the other method used handheld computerized devices and the Multi-Option Observation System for Experimental Studies (MOOSES) system. Both coding systems were used to assess social behaviors of students with emotional disabilities during writing instruction. The middle-school-aged students, all classified as having EBD, were enrolled in classes to improve their written expression. Students were assessed for on-task, off-task, and multitask behaviors. Results revealed some surprising differences. When students were relatively consistent with attendance and on-task behaviors, the methods yielded comparable results; however, when students were more disruptive and demonstrated more inconsistent behaviors, different patterns emerged. Implications and recommendations for future research and practice are discussed.

This paper aims to investigate the impact of in‐store sample promotions of food products on consumer trial and purchasing behavior. The authors investigate differences in the trial rate for free samples across different products and consumer types, as well as the impact of sampling on product and category purchase incidence. The results of this study are relevant for retailers and manufacturers who invest in in‐store free sample promotions.

The authors use data from a field study, which leveraged an actual free‐sample program implemented by a US grocery store chain. Data was collected on six different products promoted by in‐store free samples over six different weekends. The data collected included consumers' trial and purchasing behavior with respect to the free sample, as well as their attitudes towards the free sample that day and free sample promotions in general.

Free sampling is very effective in inducing trial, especially among lower educated consumers. For consumers who are planning to buy the product in the promoted category, free sampling can encourage switching from the planned to the promoted brand. For consumers who do not have such previous plans, free sampling can “draw“ them into the category and encourage category purchase. Samplers' interactions with the person distributing the sample or with other samplers at the scene also seem to boost post‐sample purchase incidence.

Despite the importance of free samples as a promotional tool, few studies have examined consumer trial and purchasing behavior with respect to in‐store free samples. This paper presents one of the first known field studies that examines this topic.

Describes a study of consumer behaviour carried out in a chocolate store involving free samples of chocolate, which found that sampling significantly increased the immediate sales of chocolates but that this effect was restricted to small amounts and to those varieties of chocolate other than the variety sampled. Discusses the implications of the findings for marketing management and consumer behaviour theory. Concludes that while sampling produces positive effects, these effects appear to be more complex than they would first seem, therefore further consumer research is needed.

Examines the practice and marketing consequences of giving out free food samples. Reports on a study, taken over a period of three days, of customers who entered a well‐established, ten‐year‐old chocolate store in a major suburban shopping mall, who received a free sample of chocolate. Shows that sampling immediately increased the sale of chocolates. Cautions that this positive effect was restricted to small purchases and to the purchase of chocolate varieties other than the variety sampled. Discusses the implications of the findings for marketing management and for consumer behaviour theory.

The goals of this paper are to determine the effectiveness of product sampling in terms of usage, to draw a consumer profile who is reactive to free samples and to determine product characteristics that would lead to free samples usage.

An experiment and a questionnaire inquiry were conducted. An outlet database was also used. Perfume, skin care and make‐up samples were given away to 500 women. In order to test the hypotheses logit models were employed.

Launching product sampling campaigns is quite effective as free samples usage appears to be high (72 per cent). Managers should give away samples of new products involving important advertising budgets. They also should offer samples of product types with a high‐penetration rate. In addition, it is better to sample well‐known brands rather than unknown ones. Moreover, the authors recommend targeting family brand users when offering free samples. Also, it is not profitable to target consumers with low‐annual spending within the product category. Finally, the authors suggest giving away samples to non‐working housewives.

This is the first paper to examine the determinants of free samples usage. Moreover, the study considers three methods of data collection. Finally, it has interesting practical and theoretical implications.

Consumer adoption of online shopping continues to increase each year. At the same time, online retailers face intense competition and few are profitable. This suggests that businesses and researchers still have much to learn regarding key antecedents of online shopping adoption and success. Based on extensive past research that has focused on the importance of various online shopping antecedents, this work seeks to provide an integrative, comprehensive nomological network.

The authors employ a mixed-methods approach to develop a comprehensive model of consumers online shopping behavior. To that end, in addition to a literature review, qualitative data are collected to identify a broad array of possible antecedents. Then, using a longitudinal survey, the model of consumer shopping intentions and behaviors is validated among 9,992 consumers.

The authors identified antecedents to online shopping related to culture, demographics, economics, technology and personal psychology. Our quantitative analysis showed that the main drivers of online shopping were congruence, impulse buying behavior, value consciousness, risk, local shopping, shopping enjoyment, and browsing enjoyment.

The validated model provides a rich explanation of the phenomenon of online shopping that integrates and extends prior work by incorporating new antecedents.

In this chapter, I proposed the use of structured behavioral analysis (SBA) as a methodological approach to address critical questions in organizational behavior research in sub-Saharan Africa.

The chapter is a conceptual paper that reviews the extant literature on research tools aimed at coding and analyzing behavior, with a particular focus on employee behavior in African organizations.

SBA requires the researcher to act as both an organizational scholar and an anthropologist. As an organizational scholar, the researcher will identify predetermined behaviors that he/she intends to study. Thus, the observation and analysis will be geared toward such behaviors. As an anthropologist, the organizational researcher will observe behaviors that are displayed by employees and managers and use them as the basis for explanation and theory building.

SBA can be used to study behaviors that often occur in African organizations, such as nepotism, corruption, the role of tribal status, and the impact of family generosity, the forced solidarity tax, and obligations on employee behavior.

Findings from SBA could help design interventions to address the detrimental effects of negative behaviors while reinforcing positive behaviors in African organizations.

As a research methodology, SBA is relatively new in the African context although some versions of the method are used in industrial/organizational psychology and ergonomics.

China is the world’s largest user market for digital technologies and experiencing unprecedented rates of rural-urban migration set to create the world’s first “urban billion”. This is an important context for studying nuanced adoption behaviours that define a digital divide. Large-scale studies are required to determine what behaviours exist in such populations, but can offer limited ability to draw inferences about why. The purpose of this paper is to report a large-scale study inside China that probes a nuanced “digital divide” behaviour: consumer demographics indicating ability to pay by electronic means but behaviour suggesting lack of willingness to do so, and extends current demographics to help explain this.

The authors report trans-national access to commercial “Big Data” inside China capturing the demographics and consumption of millions of consumers across a wide range of physical and digital market channels. Focusing on one urban location we combine traditional demographics with a new measure that reflecting migration: “Distance from Home”, and use data-mining techniques to develop a model that predicts use behaviour.

Use behaviour is predictable. Most use is explained by value of the transaction. “Distance from Home” is more predictive of technology use than traditional demographics.

Results suggest traditional demographics are insufficient to explain “why” use/non-use occurs and hence an insufficient basis to formulate and target government policy.

The authors understand this to be the first large-scale trans-national study of use/non-use of digital channels within China, and the first study of the impact of distance on ICT adoption.