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Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches – in others, new methods are potential replacements. This paper aims to explore three key trends: use of nonprobability samples, mobile data collection and administrative and “big data.”

Insights and lessons learned about these emerging trends are drawn from recent published articles and relevant scientific conference papers.

Each new trend has its own timeline in terms of methodological maturity. While mobile technologies for data capture are being rapidly adopted, particularly the use of internet-based surveys conducted on mobile devices, nonprobability sampling methods remain rare in most government research. Resource and quality pressures combined with the intensive research focus on new sampling methods, are, however, making nonprobability sampling a more attractive option. Finally, exploration of “big data” is becoming more common, although there are still many challenges to overcome – methodological, quality and access – before such data are used routinely.

This paper provides a timely review of recent developments in the field of data collection strategies, drawing on numerous current studies and practical applications in the field.

As we approach the millennium, we find ourselves in a world that places ever greater weight and significance on the outcome of polls, surveys, and market research. The advent of modern polling began with the use of scientific sampling in the mid‐1930s and has progressed vastly beyond the initial techniques and purposes of the early practitioners such as George Gallup, Elmo Roper, and Archibald Crossley. In today's environment, the computer is an integral part of most commercial survey work, as are the efforts by academic and nonprofit enterprises. It should be noted that the distinction between the use of the words “poll” and “survey” is somewhat arbitrary, with the mass media seeming to prefer “polling,” and with academia selecting “survey research.” However, searching online systems will yield differing results, hence this author's inclusion of both terms in the title of this article.

This paper aims to compare residential fixed-line telephone surveys with cell phone surveys for assessing the extent of the potential undercoverage issue evaluating the necessity and feasibility of conducting cell phone surveys or dual-frame telephone surveys in Hong Kong.

The research team simultaneously carried out a conventional fixed-line telephone survey and a cell phone survey in 2015 with similar features on survey design, sampling and data collection procedures. Two samples with sample size of 801 and 1,203 were achieved separately. Data collected were analysed to see to what extent survey findings will be biased if the sampling frame of telephone surveys is solely based on residential fixed-line numbers in Hong Kong, and if such a bias does exist, whether a survey conducted through cell phones or by adding a cell phone-only (CO) group would be an ideal solution for it.

The findings show that the cooperation rates for the cell phone survey were much lower than those of the fixed-line telephone survey. The respondents from two surveys were fairly different. However, estimates of most commonly used socio-demographic characteristics from the latter group had the least bias compared with population statistics. Supplanting the traditional fixed-line survey with a cell phone survey or supplementing it with a CO group will not make the resulting sample a better representative of the population but it will amplify the sample bias on the major social socio-demographic characteristics.

This paper empirically compares the two types of telephone surveys in a well-designed scientific study.

The aim of this paper is to review 73 survey articles relating to information technology outsourcing (ITO) published by 17 information technology journals over the 20‐year period 1991‐2010. The review focuses on seven attributes of survey methodology (i.e. information on research questions, pilot testing of the survey instrument, sampling method employed, sample size, response rate, nonresponse bias and internal validity) and ascertains the extent to which those attributes have been addressed. The main purpose of this study is to provide insights for researchers to help improve the data quality, and reliability of survey results.

Review of literature over the past 20 years (1991‐2010).

There is strong evidence that deficiencies in the administration of survey methods in ITO persist and that such shortcomings compromise rigour, and therefore need to be redressed.

Although this review is performed in an ITO context, findings are of interest and benefit to all survey researchers. The key contribution of this paper is that it provides up‐to‐date evidence regarding quality of survey research as it applies to ITO by identifying areas needing attention so that the integrity of survey research methodology can be maintained and it can continue to provide reliable findings for the advancement of knowledge.

This study provides an examination of literature dealing exclusively with an IT outsourcing survey. It can, however, serve as a guide for all survey researchers regarding the pitfalls in survey methodology.

Aims to estimate the design factors for surveys in Hong Kong. The design factor is to be used for estimating the true standard errors in surveys, using non‐simple random sampling methods. The resulting modified standard error can provide more accurate statistical computation in data analysis. Two surveys were conducted using a standard set of questions, one survey used simple random sampling; the other involved convenience sampling. Found that the design factor for surveys conducted in Hong Kong is 1.135. Notes that the two design factors found in Hong Kong are significantly smaller than those obtained overseas. Suggests this is possibly related to the Chinese people′s central tendency characteristic in expressing opinions, and that Hong Kong is a small, metropolitan city with a relatively homogeneous population.

The purpose of this paper is to compare two ways of collecting job quality data in Britain using a common set of questions. One way is through a short quiz taken by a self-selected sample and completed by clicking on a web link www.howgoodismyjob.com. The other way is via an invitation to take part in a long-running survey of working life – the Skills and Employment Survey. The survey takes much longer to complete, is carried out face-to-face and is based on random probability principles.

To be content-comparable, the quiz uses tried and tested questions contained in recent waves of the Skills and Employment Survey. Each survey comprises a nationally representative sample of workers in Britain aged 20–65 years. However, the quiz is based on uncontrolled convenience sampling prompted, in large part, by a Facebook advertising campaign, whereas survey participants are randomly selected. In this paper, the authors compare the profile of respondents and their responses to these two different modes of data collection and therefore shine a light on any biases in the samples and differences in the results respondents report.

The paper shows that while the number taking in the quiz is impressive, participation in the quiz – unlike the survey – is heavily skewed. Weighting can be used to correct some of these sample selection biases. But, even then, the picture painted by the quiz and survey data varies with the quiz under-reporting the intrinsic quality of jobs, while over-reporting on the extrinsic rewards. This suggests that how job quality data are collected can have a strong influence on the results produced.

The findings suggest that a number of biases are in operation, both in terms of those who take part and the answers they give. This makes comparison between data collected using radically different methods, at best, inadvisable and, at worst, misleading. Nevertheless, quizzes are a good way of engaging large numbers of people in public debates, gathering additional data, extending the reach of academic work and prompting action to improve working life. However, the limitation of this study is that it does not offer a true experiment of different ways of collecting the same data. The quiz and survey were, for example, not carried out at the same time, but were some 14 months apart.

Over 50,000 people took part in the quizzes reported in the paper and almost 1,300 investigated joining a trade union as a result. The reach of the quiz far exceeds the 3,306 people who took part in the Skills and Employment Survey 2017.

This paper focusses on how job quality data are collected and the consequences this has for the validity of the data gathered. This is a unique contribution to international debates about the measurement and monitoring of trends in job quality.

Online data collection is gaining momentum throughout the market research business. At the same time internet users and their online information and booking behaviour are becoming more and more important for the travel and tourism industry. This paper aims to investigate this issue.

The paper researches internet users' travel and information/booking behaviour through online surveys. However, this approach is prone to critical methodological limitations. One of the main issues in this respect is the question of proper definition of the universe and sampling procedures. The paper shows today's chances and limitations of sampling using list‐based e‐mail invitations and online access panels.

Results indicate that sampling method and length of field time have a substantial influence on response rates. It can further be shown that results from online travel research differ from results obtained in face‐to‐face interviews even when focussing on the same target group.

As long as online research differs from research on internet users to such an extent, online surveys seem to be rather a good complement than a substitution for more traditional research methods.

The paper shows the limitations and chances of online travel research based on the unique comparison of data from a face‐to‐face and online access panel surveys.

This paper shows several results obtained from the first investigation made in Spain using Dillman's total design method for mail surveys. In the spring of 1998 a survey was carried out on consumer behaviour in one particular Spanish region (Navarra). The response rate was 68.3 percent. One month later, a team of professional interviewers interviewed the people who did not respond to the mail survey. The objective is to compare the results obtained by these interviewers with an estimation of the non‐response after using several different methods and a group of adjustment procedures.

The total design method (TDM) for mail surveys has produced some wonderful results in several countries in Northern and Central Europe, but as far as one can gather it has never been used in any of the countries of Southern Europe surrounding the Mediterranean. The excellent results obtained from mail surveys in the USA, and some of the findings confirmed by disciples of Dillman in several European countries, led to carrying out the first investigation in Spain using TDM through mail surveys. With the aim of resolving some of the above‐mentioned questions, it was decided to make the first‐ever investigation using TDM within Spanish society.

The results obtained by applying the total design method to a Mediterranean country do not differ greatly from data obtained by other researchers on the efficiency of mailing surveys in other countries. This fact forces one to have serious doubts about the declarations of some experts who place the response rate for mailing surveys at 40 percent in Spain. In this paper, different strategies to reduce the impact of non‐response in a mail survey are outlined. First, a second interview was carried out with a subsample of the interviewees who were non‐responders, with the aim of finding out more about the characteristics of those who do not respond. Later, a strategy of weighting was used using CHAID to identify the best predictors from among the set of variables available.

In the South of Europe there is very sparse use of mail surveys, while there is great use of face‐to‐face surveys: this is the opposite of the tendency in other countries, where telephone surveys are supplanting the face‐to‐face interview. This is the first research about non‐response in mail surveys in the South of Europe.

Many accounting researchers use direct mail survey questionnaires as a means of data collection. There are many advantages in using mail surveys. For example, surveys are a cost‐effective and efficient means of collecting research data and they provide a means of obtaining data from a geographically diverse population. However, there are several potential problems associated with the use of questionnaires in general and mail survey questionnaires in particular. These include sampling bias, low response rates, response bias, and poor questionnaire design. Numerous suggestions and procedures have been proposed in the literature to reduce the impact of these factors — unfortunately, most of these suggestions have gone unheeded. A study recently published in this journal (Guilding and Kirman, 1998) is critiqued in order to point out the potential limitations associated with using survey questionnaires, and to indicate what researchers can do to mitigate the effects of these problems.

This paper introduces a Bayesian two-sided group chain sampling plan (BT-SGChSP) by using binomial distribution to estimate the average proportion of defectives. In this Bayesian approach, beta distribution is used as a suitable prior of binomial distribution. The proposed plan considers both consumer's and producer's risks. Currently, group chain sampling plans only consider the consumer's risk and do not account for the producer's risk. All existing plans are used to estimate only a single point, but this plan gives a quality region for the pre-specified values of different design parameters. In other words, instead of point wise description for the designing of sampling plan based on a range of quality by involving a novel approach called quality region.

The methodology is based on five phases, which are (1) operating procedure, (2) derivation of the probability of lot acceptance, (3) constructing plans for given acceptable quality level (AQL) and limiting quality level (LQL), (4) construction of quality intervals for BT-SGChSP and (5) selection of the sampling plans.

The findings show that the operating characteristic (OC) curve of BT-SGChSP is more ideal than the existing Bayesian group chain sampling plan because the quality regions for BT-SGChSP give less proportion of defectives for same consumer's and producer's risks.

There are four limitations in this study: first is the use of binomial distribution when deriving the probability of lot acceptance. Alternatively, it can be derived by using distributions such as Poisson, weighted Poisson and weighted binomial. The second is that beta distribution is used as prior distribution. Otherwise, different prior distributions can be used like: Rayleigh, exponential and generalized exponential. The third is that we adopt mean as a quality parameter, whereas median and other quintiles can be used. Forth, this paper considers probabilistic quality region (PQR) and indifference quality region (IQR).

The proposed plan is an alternative of traditional group chain sampling plans that are based on only current lot information. This plan considers current lot information with preceding and succeeding lot and also considers prior information of the product.

This paper first time uses a tight (three acceptance criteria) and introduces a BT-SGChSP to find quality regions for both producer's and consumer's risk.