BLUE-ETS Conference on Burden and Motivation in Official Business Surveys

Statistics Netherlands, Heerlen, March 22 & 23, 2011

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Motivation in business surveys

Vanessa Torres van Grinsen1, Irena Bolko2, Mojca Bavdaž 3 and Silvia Biffignandi4

1 Utrecht University & Statistics Netherlands, e-mail: v.torresvangrinsven@cbs.nl2 University of Ljubljana, e-mail: irena.bolko@ef.uni-lj.si

3 University of Ljubljana, e-mail: mojca.bavdaz@ef.uni-lj.si4 University of Bergamo, e-mail: silvia.biffignandi@unibg.it

Abstract Businesses are often legally obliged to report data timely and accurately to the NSIs but they are increasingly reluctant to do so because of allegedly high actual and perceived response burden. Huge reductions in actual response burden that NSIs already achieved have not made similar impact on perceived response burden. Some knowledge has already been obtained on perceived response burden while knowledge on its positive counterpart, i.e. motivation, has still been lacking. The paper thus aims to build a framework for motivation in business surveys based on thematic analysis of qualitative interviews with businesses in the Netherlands and Slovenia. It also suggests several opportunities for NSIs to improve motivation in business surveys.

Keywords: individual motivation, organizational motivation, value for business

1 Introduction

One of the ten fundamental principles of official statistics states that “data for statistical purposes may be drawn from all types of sources, be they statistical surveys or administrative records” and that statistical organizations should “choose the source with regard to quality, timeliness, costs and the burden on respondents” (United Nations Statistical Commission 1994). Costs and response burden figure as a constraint to achieving high quality of official statistics (Eurostat 2003). In order to mitigate this constraint, NSIs have been replacing some of the direct data collection with more cost-effective administrative data sources. This trend has been further fostered by the Action Programme for reducing administrative burdens in the European Union in January 2007 (European Commission 2010). However, various characteristics of administrative data (e.g. concepts, specifications, periodicity, timeliness, detail, coverage etc.) may not be suitable for users’ needs (Bøegh-Nielsen 1997). Taking into account the increasing demand for data, it is obvious that substituting business surveys has a limit. So business surveys remain an

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indispensable part of data collection; they may even become more demanding given the provision that basic data may be collected elsewhere. NSIs usually have a legal mandate for collecting data so businesses are legally obliged to report data timely and accurately but they are increasingly reluctant to do so. This has negative consequences for the NSIs. Many respondents in business surveys reduce the response burden imposed on them by simplifying their survey task, e.g. by using business concepts instead of requested statistical ones, by disregarding exceptional or marginal activities, by sticking to established response strategies etc. (Bavdaž 2010a). Some respondents even choose not to respond. Just because of inaccurate completion of business questionnaires, NSIs incur editing costs that may amount to 30 % or even 40 % of total data collection costs, with costs of annual and rarer surveys being higher than those for more frequent surveys (Black 2009; Norberg 2009). Although for political reasons, debates in official statistics have been focused on actual response burden, the time has come to focus on perceived response burden as this may be more relevant for accurate and timely reporting (cf. Gravem et al. 2011; Haraldsen 2010; Willeboordse 1997). As the expression “burden” bears a negative connotation and implies the relevance of only one aspect of the survey task, suggestions have been made to emphasize the positive counterpart of the burden, namely to focus on motivation in business surveys. According to Ryan and Deci (2000), to be motivated means to be moved to do something; a person who feels no impetus or inspiration to act is thus characterized as unmotivated, whereas someone who is energized or activated toward an end is considered motivated. Deci and Ryan (1985) also distinguish between different types of motivation based on the different reasons or goals that give rise to an action. We thus start from the assumption that motivation plays an important role in business survey response. The aim of this paper is to get insights into the motivation in business surveys. More specifically, we are interested in motivation to participate in business surveys and provide accurate and timely response. The approach is based on the premise that motivation for these, usually separately treated decisions, has a common basis. At least mandatory business surveys conducted by the NSIs try to make (though not always successfully) the decision for survey participation irrelevant. Also, it is not straightforward in business surveys whose motivation to study as we have different business participants and various elements of business environment potentially contributing to measurement errors (Bavdaž 2010b). Among different business participants we decided to focus on respondents because they play the most prominent role in the survey response process; and among various elements representing the context for business survey response we decided to focus on organization because of its potential impact on motivation from management. The decision for the respondent and the organization is also consistent with Tomaskovic-Devey et al. (1994) who argued that both respondent’s and organization’s authority, capacity and motive contribute to non-response.

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The paper is based on data from the international BLUE-ETS project. At this stage of research we focused on qualitative data from two participating countries, namely the Netherlands and Slovenia. Collection of data from businesses was carried out between December 2010 and February 2011 based on common methodology. Knowledge of what drives the motivation in business surveys should enable us to develop more effective strategies to enhance survey participation and reporting. The paper is structured as follows. We start by presenting the methodology of the study (Section 2). We proceed to presentation of results (Section 3); we first address organizational perspective on motivation and then the individual perspective on motivation. We conclude with lessons for the NSIs that follow from the findings and open issues that require further consideration (Section 4).

2 Methodology

Data come from international research that seeks to understand what motivates businesses for participation and accurate and timely reporting in NSI surveys, and forms part of the BLUE-ETS project involving Statistics Netherlands, Statistics Norway, Statistics Sweden, Statistical Office of the Republic of Slovenia, University of Bergamo and University of Ljubljana. In the first phase of research we carried out a number of qualitative interviews with various experts on the use of NSI statistics by businesses. The outcomes served as input for the development of a topic list for an interview guide to be implemented in qualitative interviews with businesses. After conducting some pilot interviews and further discussions among participants, the interview guide was created around three broad issues in relation to research questions:

• Use of data in businesses shedding light on potential link between business survey response behavior and fact-based decision making

• Motivational aspects in business survey response behavior. • Links within businesses between people reporting data to the NSIs and other

surveying organizations (respondents to business surveys) and people who use internal or external data as part of their job (data users), e.g. people involved in various analyses and production of reports, people at the managing positions etc.

The interviews were conducted as semi-structured interviews with a fixed list of topics within the three broad issues but only suggested list of questions within each topic. Sample size varied by country from three to nine businesses depending on financial and other restrictions. Selection of businesses aimed at maximizing heterogeneity in collected data. Two criteria were judged essential to achieve this: size class and economic activity. Size classes were defined in terms of the number of employees: small (less than 50),

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medium (at least 50, less than 250) and large (at least 250). Regardless of the total number, we aimed at interviewing the same number of businesses in each of the three size classes. We also aimed at businesses with different economic activities (difference established at least the level of divisions in the NACE classification). We decided beforehand that selected activities should have the following characteristics:

• being important for the economy (e.g. with high contribution to the GDP) ; • having many businesses; • having a large share of small businesses among all businesses.

We exposed economic importance because of the attention (and response burden) such activities may get. We chose activities with many businesses so that our findings could be generalized to many similar businesses. We chose activities with many small businesses because of their relatively high response burden. These characteristics should help us get insights that would be relevant for important economic segments, many businesses in general and many small businesses in particular. We also kept in mind other criteria that were not explicitly defined, e.g. services vs. industry, internationally oriented vs. locally oriented business, foreign-owned vs. domestically-controlled, location (e.g. capital urban area vs. other), young vs. well-established business and management etc. Initial contacts were established by phone. The recruiting strategy was to start with one interview per business agreed in advance. In some businesses, we targeted respondents to business surveys while in others we targeted data users (in particular accounting, economic, analytical, (quality) control departments, etc.). To get more than one interview per business, we used “foot in the door” technique. Once the first interview was done we tried to get another interview with a different target person. This was partially successful. Interviews were recorded to facilitate detailed transcription and in some cases gifts were given before or after the interview as a token of appreciation. This paper is based on interviews conducted in the Netherlands and Slovenia. It focuses on qualitative data relevant to the topic of motivational aspects in business survey response behavior. Table 1 provides some details about the selected businesses and respective interviewees. The first step in our analysis was making a transcription of the recorded interviews, and doing this as detailed as possible. That is, a verbatim account of all verbal utterances is given. We then searched for themes in the data that related to our specific question of interest, namely motivational aspects in business survey response behavior. The thematic analysis (cf. Braun & Clarke, 2006) mainly relied on an inductive, “bottom up” approach. However, we have to acknowledge that during the development of the interview guide we already had some analytic preconceptions and some background knowledge of potentially relevant or related theories like the theory of planned behavior and the theory of

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organizational survey non-response. This was partly reflected in the topics of the interview guide.

Table 1: Details about interviews included in analysis Interview Country Interviewee Size class Activity Gift

1 Netherlands Owner Small Trade Yes

2 Netherlands Respondent to business surveys Medium Manufacture of metal products Yes

3 Netherlands Respondent to business surveys Large Retail Yes 4 Slovenia Data user Small Construction Yes 5 Slovenia Respondent to business surveys Small Transport Yes 6 Data user Yes 7 Slovenia Respondent to business surveys Medium Specialised retail

(with some wholesale) Yes 8 Slovenia Respondent to business surveys Medium Specialised wholesale Yes 9 Data user No 10 Slovenia 2 respondents to business surveys Large General retail No 11 Data user No

12 Slovenia Data user & respondent to business surveys

Large Manufacture of metal products No

Nevertheless, as far as possible, we followed a data-driven process of coding of collected data without a priori trying to fit them into a pre-existing theoretical model. Further on, we searched for themes at the semantic or explicit level within the realist/essentialist paradigm, where we assumed a simple, largely unidirectional relationship between meaning and experience and language. Themes sometimes applied to a longer passage of the interview while other times several themes applied to an interviewee’s turn of speech.

3 Results This section presents results of a thematic analysis of interviews with respondents to business surveys and/or data users in businesses in the Netherlands and Slovenia. The results show what themes were identified as driving motivation for survey participation and accurate and timely reporting of requested survey data. We distinguish between themes identified at the organizational level and those identified at the individual; we organize the presentation of results accordingly. We support the presentation of themes with data extracts, that is quotes from interviews labeled with the country code (NL = the Netherlands; SLO = Slovenia), the size class (S = small; M = medium; L = large) and the interviewee position (R = respondent to business surveys; DU = data user). Every theme is accompanied with an argument about how it relates to the motivation.

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Corporate social

responsibilityAttention Prioritizing Statistical hub

Emotional aspects

Habits & routines

Worth attached to survey task

Obligations

• Experiences in surveys• Personal ties withstatistical organization

• Empathy & sympathy• Mood

• First time vs. recurrentcompletion

• Maintaining responsepractices and changes in reporting

• Profession• Challenges

• Value for business• Survey sponsor• Beliefs & stereotypesabout statistics & surveys

• Mandatory reporting• Contractual basis• Tasks arising from

job description

Figure 1: Motivation in business surveys

3.1 Organizational motivation

Corporate social responsibility

Both large Slovenian businesses claimed that they take part in practically all surveys that they get requests for. “I don`t believe we ever rejected any survey request, at least not in my department.” (R, L, SLO) Reason for a great number of requests they are receiving was expressed through belief that “we are a large company and our data definitely mean something. That`s why we are included in so many surveys and researches.” (R, L, SLO) On the contrary, in the Netherlands both respondents of the large and medium businesses commented that they only responded to mandatory surveys, though in the large company they understood that “As a huge company you’re just part of that sample. You cannot say this year we will not do this, huge company so...” (R, L, NL)

As one of the interviewees stated, their company strives for complete transparency of the business they are running because of their stock-exchange listing and thus it is agreed to participate in all surveys. When it comes to data, concern about public image has broader scope than just participating in surveys, it also includes attention given to data quality: “Data we are producing need to be accurate, that`s the most important thing. We are informing the public, so we must provide accurate data.” (DU, L, SLO) They also carefully follow the news on their company in the media: “Sometimes qualitative information could

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ruin our image, reputation, although our quantitative data is showing a positive direction. We have to be aware of that.” (DU, L, SLO)

The “transparency rule”, however, is not always supported by all employees: “The top management requests us to participate in as many surveys as possible in order to be more transparent, but if they were to complete the questionnaires, they would probably react more like – not the NSI again, what do they want now?” (DU, L, SLO)

In addition, large companies sometimes distinguish between the NSI and commercial agencies with regard to the kind of data they are supplying to them: “To the NSI we are providing everything and we know that these data will remain confidential there in a way that no one would be able to identify us when the data is published. For the rest of the institutions that are requesting data we have a rule of providing only those data that has already been sent to the public.” (DU, L, SLO)

Attention

Despite applying very strict rules for confidential data (“No confidential data goes out of company without being previously approved by top management” (R, L, SLO)), reporting in general is not given much of attention by superiors and top management, especially not in small and medium businesses, while in large companies some very rough or implicit check by superiors was mentioned. Cooperation between several persons is often required when completing the data. Usually it is a coordinator (who may also figure as the contact person) who collects the information. In almost all of the included businesses explicit checks by superiors were not made. Only in very few cases, interviewees reported that superiors know what the respondents to business surveys are doing and if they need to sign they understand (from a glimpse on the form) if the figures seem correct: “Well, they (superiors) don`t check, but actually they know.” (R, L, SLO) Of course, responsibility for accurate figures stays with the respondent: “You as the person who fills in the questionnaire are responsible for the accuracy of data. R, L, SLO); this seems to hold even when the respondent has to turn to superiors to get data from. In the Dutch cases it was observed that reporting tasks were done by just one person: “My direct colleagues in fact don’t know anything about responding.” (R, L, NL), and checks are not done even in the large companies: “Well, the managers are not concerned with the NSI at all. Concerning the NSI almost nobody knows what’s still open and what still needs to happen.” (R, L, NL) Another respondent also does not see or hear anything about it. (R, M, NL)

Reporting statistics appear to be routine work and superiors and top managers only give attention to it when something goes wrong (e.g. when they forgot to report), if reminders from the NSI are received (“Of course then they ask why’s that not finished yet?” (R, L,

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NL) or indirectly when they notice that a person from the department that is responsible for data reporting is on sick leave (“They ask us if we will manage to do everything in time, but they ask in general, they don`t mention statistical reporting in particular.” (DP, M, SLO)).

Prioritizing

There is usually always a deadline for completing the questionnaire and practically all the companies that were included in our study, reported that they do their best to complete the questionnaire in time although they do not start to complete it immediately they receive it and it often happens that there is a delay of some days. Priority is given to work tasks although they “understand the importance of having this ready in time” (R, L, NL). Top management seems to get similar data that company is reporting to the NSI: “I report to the top management and to the NSI at the same time, it`s the same data maybe just slightly modified. But priority is in-house – we are primary responsible to our managers.” (DP, M, SLO)

The strategies of dealing with questionnaires are quite similar in the companies regardless the size and could all be labeled as postponing: “First you put it aside for a while, you do your own work, but till the deadline you try to complete it”. (DU, S, SLO) “So then there’s so much that has to be figured out and at last the report has to be finished and then I just don’t have time for the survey” (R, L, NL) “If I have something more important to do than I just put it aside.” (R, L, NL) “Well, eh, it does not have the highest priority, let me put it like that”. (R, M, NL)

Although postponing is so widespread it does not happen in all cases: “We check how much time there is until the deadline and if we have some free time in this period, then we complete the questionnaires. Otherwise, if we are busy with our own tasks, we try to postpone the deadline if it`s not strictly set, we ask if we could delay for few days up to a week.” (DU, L, SLO) One of the interviewees (R, L, SLO) also explained that they estimate in advance how much time it takes to complete the survey the first time they are participating. This information is then helpful for future scheduling. One of the most common reasons for delay mentioned was unavailability of the requested data by the deadline. The NSIs acknowledge this problem and allow a couple of days delay: “We don`t have available all the data at the deadline and as we are a large company that provides a great share of aggregated data, we made an agreement with the NSI that we report with a few days of delay in order to assure accurate and reliable data.”(DU, L, SLO) “And only when I receive that definite signature (...) then we can continue with this.” (referring to the survey) (L DP NL) Not only the daily operations in the company (e.g. having other tasks to accomplish first), but also the extraordinary situations, sometimes due to the turbulent happening in the business environment (e.g. reorganization within company due to economical crisis or take-

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over) has a (negative) effect on timely response as the surveys are left aside and thus responding is postponed to an even larger extent: “We had some very busy wild year when the company was taken over. So at one moment we were later every time with responding.” (R, L, NL) “A couple of years, when we were in this fusion the surveys were left aside.” (R, M, NL)

Statistical hub

Respondents throughout several interviews claimed that questionnaires “come” to them. It seems that some departments and people are more likely to receive survey questionnaires. One of the respondents (DU, L, SLO) who could be regarded as a “receiver” reported that practically all the questionnaires are sent to him either through the secretary office or directly from institutions that are requesting data. Then he decides who is going to be responsible for questionnaire’s completion. Decision is based on data availability – the questionnaire goes to person that is in charge of or is able to access the requested data. Problems arise when address or name on envelope is wrong. Sometimes the questionnaire is send to the person who used to be responsible for data reporting but might not work in the company anymore. This could provoke delays in reporting as well even if originally such approach was designed to avoid them.

3.2 Individual motivation

We clustered themes relevant to individual motivation in four groups: emotional aspects, habits & routines, worth attached to survey task and obligations.

Emotional aspects

Experiences in surveys. When talking about experiences in surveys in general, respondents were usually complaining about the length of the survey and the time it takes. In some cases the questions are judged as quite demanding (e.g. requests to classify in detail, the need to sum up); data might not always be already available. Personal ties with statistical organization. We also found that a personal tie and friendly relationship with any representative of the NSI enhances good survey participation. This friendly way of relating can have several expressions. One of them would be in the personal relationship with the “account manager” that is responsible for the contacts with the business on behalf of the NSI. Apart from this personal relationship, some mentioned that the practical help offered by this “account manager” is very valuable: “So past years I’ve been in contact fairly often to steer things better and to better achieve the necessary information and being able to complete questionnaires better. Because I missed some

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background and I was thrown in the deep so it helped me a lot yes.” (R, L, NL) Another way this personal tie is expressed is in the friendly communication with people from the customer service which are prone to respect the needs of the respondent. This would happen, for example, in the case a company needs some extra time for responding. Lastly, a friendly tone and language in the letters received by the company seem to be valued: “Very neat. I cannot say anything bad about that. Maybe they are even too sweet. (...) But that’s the right way to cooperate. If any of the counterparts attack then somebody might get blocked and then you are even more far from home.” (R, L, NL). And vice versa, “If the requests are not polite, we cancel them immediately.” (DU, L, SLO)

Empathy & sympathy. This theme also came out when discussing the participation in various non-NSI surveys or interviews. Respondents seem to understand the position of interviewers or show some compassion: “Sometimes I feel sorry for them, so much solicitation, dealing with all impolite reactions of respondents... I wouldn`t be able to do this work.” (DU, S, SLO)

One very good example is the reason why certain respondents agreed to participate with the interview we did for this paper. One of the respondents mentioned a very specific reason for which to make an effort to respond as accurately as possible: “Because my father used to work at the NSI, of course, I know a bit what happens with these figures (...). If any time a tenth behind the comma was not good then there would be stress and panic.” (R, L, DP, NL)”

Mood. Our data also indicate that personal mood affects the decision to respond and the way the respondent actually responds. This theme seems to work mostly on participation in case of responding to non-NSI surveys or interviews: “When I`m in a good mood then I usually participate in all those surveys, but if I`m in bad mood then I probably reject.” (R, M, SLO)

Habits & routines

First time vs. recurrent completion. Collected data suggested that over a course of years respondents become more happy and content with the work they are doing presumably because recurrent completion reduces burden: “Well, I start enjoying it much more every time. (…) In the beginning because you`re still looking for your way it`s never pleasant.” (R, L, NL) On the other hand, the negative side is that the task gets boring over time: “If you do the same thing every year, then it gets boring.” (R, L, NL)

Maintaining response practices and changes in reporting. As suggested above, reporting seems to run on a routine basis. “So at least I personally have a structure that I fill in the questionnaires in a certain way and that I maintain this structure over the years” (R, M, NL). This routine which makes the completion easier and less time-consuming (“Well, yes,

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then you have a certain way of getting out of things. And if something changes, yes, then I have extra work but, ehem, you then finally figure out how to fill it and then it runs again smoothly.” (R, M, NL)) is then considered more important than reporting accurately: “We keep the method the same over the years to maintain comparable figures. Ehm, a mistake, if you make a mistake in 2008, then you have to do the same in 2009 because then at least the trend is visible.” (R, L, NL)

Maintaining such a routinized response practices implies that any changes in the surveys are accompanied with extra work: “It happens that one year all changes and then you have to report in a new way, change everything and then even adjust data for the preceding years.” (R, L, SLO) Despite the impression of stableness of data providing activity, respondents did mention on several occasions that changes in reporting occur. Adapting to novelties is most of all reported to be time-consuming. “Well, yes, then you have a certain way of getting out of things. And if something changes, yes, then I have extra work but, ehem, you then finally figure out how to fill it and then it runs again smoothly.” (R, M, NL). “It happens that one year all changes and then you have to report in a new way, change everything and then even change data for the previous years” (R, L, SLO)

Profession. We have interviewed people with different kinds of profession, though most of them worked at the financial department of the company. Interviewees referred to a specific attitude belonging to their profession (e.g. financial controller or accountant) as something that included an inherent impetus for being as accurate as possible: “Yes, as a financial man I was drilled previously. (...) I’m very strong in basing everything. (...) The records, that’s the only truth here. (...) It’s the source, the truth.” (R, M, NL)

Challenges. When being asked about the challenges that data reporting offers, the respondents were quite direct: “Challenges? [laughing laud] No challenges at all!” (R, M, SLO). “It`s not the highest challenge to complete those lists.” (R, M, NL) Challenges were more often associated with work they do in general and not particularly with reporting to the NSI: “I`m a searcher in my soul. It`s a challenge for me to search for new ways of obtaining and using data.” (DU, L, SLO) They are also associated with performing new, demanding tasks: “(...) that’s a challenge. So I like to do that, yes.” (R, L, NL)

Worth attached to survey task

Value for business. Companies seem to find their own data more important: “I would say that we are an introvert business as we are very specialized and thus focused extensively on our own data,” (R, S, SLO) compared to statistical data. “I`m not saying that statistics is a lie, but it`s not so important for us, operational workers, maybe is more useful for managers and directors. “ (DU, M, SLO) They might find these data interesting: “Maybe

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these data are interesting for general knowledge, but we don`t use them at business decision making.” (DU, S, SLO) However, uselessness is an expression that appears throughout several interviews in small and medium businesses. On the other hand, large businesses expressed quite the opposite opinion: “Having no statistical data is like driving a car by night without lights on – you have no idea where are you going to.” (DU, L, SLO)

When speaking about statistical data, large companies prefer to obtain “raw” data as they are doing their own analysis, according to their own method “I don`t need any graphs or content, I`m only interested in numbers” (DU, L, SLO). But when addressing top management, interviewees in large businesses agreed that it is better to graphically present the data and thus make them more visible. Value for business seems much more obvious in some voluntary surveys where respondents referred to the exchange of (free!) reported data for (paid!) useful information: “I know, well ehm we buy information at [commercial bureau], so about companies and sometimes they ask us information about certain companies and payment terms and behavior.” (R, M, NL) Survey sponsor. In our interviews we found that results based on reporting to the NSIs are associated with usefulness for the government, society, other businesses etc. As noted above respondents in large part did not see any particular value of survey results for their own use, but they did find statistics useful on a more general level: “Sometimes I noticed in media some statistical data mentioned. It`s interesting but I don`t know why I would personally use it. I think it`s more useful for economy, for tourism, depends why they need it,” (R, M, SLO); for some imaginary others: “I don’t see it myself but I understand that these figures are useful for people and they base things on that,” (R, M, NL); for the government: “Ehm, yes, I think everybody has to contribute what one can, yes, to the total picture that has to be right and that it’s going to be used by politics (...) or another governmental institution,” (R, L, NL); or for other companies: “But still these data must be collected. Although they are not useful for us, maybe some other companies are using them.” (DU, M, SLO)

Some respondents went further and expressed doubts: “Honestly, I find some of the surveys useless and I have no idea why would they be used for. However, I believe that some statistical data needs to be collected, but I want to see the good reason for doing that. I don`t want to do them just because they need to be done and then they would end up stored in some office drawer,” (R, L, SLO) “In that questionnaire there are really strange parts. (...) Then I have to dissect things (...) and then I don’t see the importance of that.” (R, L, NL). Some were also very critical about the impact of statistics: “It`s not useless at all, it`s very important. But the problem is that the government when they see the results, from those results they don`t react. And now in the time of economic crisis, when we do need reaction, otherwise it will go worse.” (R, M, SLO) Doubts came up especially when respondents knew they were not able to provide exact figures due to lack of data in their

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information system; they then questioned the use of such figures and the work necessary for producing these figures that nevertheless would not be exact. Beliefs & stereotypes about statistics & surveys. We noticed an interesting phenomenon in Slovenian interviews. On one hand respondents were commonly expressing some general feeling of burden with statistical reporting, for instance: “reporting is just causing extra work”, “we don`t see how these data would be useful for our company” and even quite extreme statements such as “reporting is an inevitable evil”. On the other hand, however, when being asked a specific question (e.g. how much time do you need for reporting, how well do you understand the questions?), the answers were quite the opposite, for instance: “Reporting doesn`t take so much time and effort” (R, S, SLO), “Maybe just one or two questionnaires are a bit more demanding and time consuming, the rest goes quite fast” (R, L, SLO); “Questions seems to be clear enough, at least the majority of them, but for the few ambiguous ones we are able to get quick and efficient additional explanation from the NSI (R, M, SLO)”.

Obligations

Mandatory reporting. When it comes to participating in NSI surveys, obligation to participate seems to be the primal and major motivation: “Legal mandate is the only reason to comply with requests.” (DU, S, NL) If it is left up to companies to decide whether to participate or not, then it could as well happen that the request to take part in a survey is rejected: “Reporting to NSI is obligatory, so we have to do it. The rest we decide upon our current capacity – if the questionnaire is short and does not request extra search for data, than we do it, otherwise it is questionable if we are able to participate... (...) Yes, I have to say that if other things come from other parties or institutions that are not mandatory but voluntary then I think we often withhold from that.” (R, M, SLO).

Contractual basis. Apart from legal obligation to report to the NSI, some businesses are also obliged to report to organizations they are cooperating with. This obligation may be based on a contract. Similar to mandatory reporting to the NSI, this kind of reporting does not provoke any second thoughts: “I don`t think about it. We have a contract to report and I just do what I have to. (...) And the same for NSI, we are obliged to report, the law is like a contract for me.” (R, M, SLO)

Sometimes they have contracts with commercial bureaus to which they provide confidential company data in exchange for data interesting for the company: “We have commercial bureaus, yes. We, ehm, have a deal with them.” (R, L, NL) The response burden may not be negligible, e.g. weekly reporting. Tasks arising from job description. It is interesting to note that in some cases the obligation to respond is neither checked nor doubted but simply accepted as part of the job:

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“I haven`t checked, but I assume it`s obligatory to report. If you are chosen and you agree on something, than you have to do it no matter what.” (R, S, SLO) “For me it’s a fact that I have to fill them in and that’s just how it is.” (R, M, NL).

4 Lessons for NSIs and further research The proposed framework for motivation in business surveys suggests several opportunities for NSIs to improve motivation in business surveys. In this section, we shortly describe some of the most promising approaches. We first address some opportunities with regard to organizational motivation. Importance of corporate social responsibility for motivation suggests that communication strategies of NSIs may be more persuasive in including statistical reporting among the topics towards which businesses have to act responsibly because of their societal importance. Statistical reporting to NSIs also suffers from the lack of attention at the management level, which is not surprising given that the NSIs rarely have a prominent position in the media. This suggests that management in businesses should also get some attention in communication of the NSIs. The framework also suggests the usefulness of having a statistical hub in a business, a single contact point or a single department to turn to but this requires a system from the NSIs that support collection and maintenance of such information. As for individual motivation, NSIs already largely avail of mandatory reporting. Other opportunities open up for the NSIs through personal ties with people in businesses. These ties typically developed sporadically as people in the NSIs used their natural communication skills. NSIs can, for example, learn from the business world how to train their staff to better serve their “clients”. This opportunity goes hand in hand with the system that would support the identification of a statistical hub in the business. It could also facilitate development of strategies that would respect the peculiarities of professions and their impact on the motivation. It could also support the identification of first vs. recurrent completion of the questionnaire; NSIs typically assume a passive role and wait for the business to make the first move and contact them until it is too late and the errors are committed and later (hopefully) discovered during the editing step of statistics production. A proactive approach in cases where first completion is expected might have an important impact on the individual’s motivation and all subsequent survey participation. Even mood that seems completely out of NSIs’ control may be improved, for instance, by making messages as friendly as possible. But if we are to choose one single aspect that seems most promising, that would be the value for business because our data suggest that this drives people to internalize reporting. Before concluding it has to be noted that the proposed framework has been built on a small scale study in two countries. No systematic differences between countries were observed with regard to the motivation in business surveys though this might change when more cases and more countries are included in analysis. New relevant themes might also emerge.

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The framework may somewhat change when considering voluntary business surveys or survey organizations other than NSIs. It may also be extended to include more specific aspects when applied to a particular survey with specific characteristics. Furthermore, the proposed framework needs to be critically evaluated with regard to other relevant or related models, frameworks and studies, for instance, the theory of planned behavior (Ajzen 1991), the theory of organizational survey non-response (Tomaskovic-Devey et al. 1994), a response model (Snijkers 2008), a study of respondent’s opinion about surveys (Loosveldt and Storms 2008), a study of respondent satisfaction and burden (Wenemark et al. 2010) etc. Last but not least, although the framework suggests what needs to be addressed to affect the motivation in business surveys, it does not tell how strong this effect might be and how exactly to exercise it. This also awaits further research.

Acknowledgements The research reported herein was funded by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n°244767. The views expressed in this paper are those of the authors and do not necessarily reflect those of the organizations they are affiliated with.

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