Open Research Online Planejamento de Questionários: Uniﬁcando conhecimentos em Pesquisa de Mercado e Psicometria Journal Item

In this study, practical specifics on developing questionnaires for technical and/or academic purposes are presented, considering the functionality and contextualization in administration research. From this, it was proposed to theoretically deepen the questionnaires operationalization as research instruments. Based on a bibliographic study, we discussed the proper planning of instruments for sorting, construction, application (sur-vey) and analytical possibilities, considering the concepts of reliability, validity, and precision. Examples from the literature were used to demonstrate the useful application of questionnaires in managerial contexts. As a contribution, this study advances in the compilation of knowledge in psychometrics and marketing research, which enable a broader spectrum on the usability of instruments for decision making with greater methodological robustness.


Introduction
The fundamentals for designing an investigation, whether for addressing aca- Accordingly, when the literature is not sufficiently complete and comprehensive, or its basis is not adequately systematized, empirical research is required (see, SOARES;PICOLLI;CASAGRANDE, 2018). Thus, the research process requires specific tools that meet the empirical research objectives, such as questionnaires and interviews or observation scripts.
Specifically, in studies that encompass the investigation of phenomena linked to social, technological, and human interaction from different contexts of health, humanities, and applied social sciences, the use of questionnaires is predominant and extensively spread (GENES et al., 2017;GIL, 2019;MARKUS, 2019). The questionnaire becomes a central data collection tool, whose theoretical-empirical treatment is a condition underlying its conception, and the implications of its use are a catalyst for discoveries (WILKINSON; GIBBS; WAITT, 2020).
In operational terms, a questionnaire is a tool that comprises a group of standardized and pre-established items, questions, or issues, whose purpose is to measure characteristics and/or attributes related to phenomena, people, processes, or organizations. Its fundamental assumption is the guarantee that technical-scientific aspects will be taken into consideration, aiming at the accuracy and precision of the research (MALHOTRA, 2011;HAIR et al., 2014). Therefore, the development of a questionnaire is a rigorous and detailed process that comprises the writing, order-

RESUMO
ing, and presentation of items (also known as questions), which are compulsorily linked to the administration of the questionnaire itself and the idiosyncrasies of data collection procedures (OLSEN, 2015;GEUENS;DE PELSMACKER, 2017).
Several researchers only discuss the planning and development of questionnaires by focusing on the breadth of their applications (e.g., FINK, 2002;MOREIRA, 2009;VIEIRA, 2009;ZHANG et al., 2017;BRACE, 2018). However, some operational and daily practice details are still unexplored or not clear enough.
This article aims to theoretically deepen the operationalization of questionnaires as research instruments, from a practical and functionalist perspective, to provide an integrated view among psychometrics and marketing research for the questionnaire development protocols. Considering the management research context -from individual and organizational diagnosis to market analysis -, the successful operationalization of questionnaires can promote research quality and reliable results. For this approach, a hypothetical case was proposed to demonstrate ways to plan questionnaires.
It becomes even more relevant when researchers (including professors, students, consultants, managers, and market analysts) are eager to access the options for developing and applying questionnaires through digital tools and online platforms, which complementarily bring facilities for data collection, tabulation, and analysis (STOET, 2017;MALHOTRA, 2018). This indicates an expansion in the dissemination and use of questionnaires as data collection tools, although the principles for assessing their instrumentation quality remain the same: reliability, validity, and objectivity (SHAUGHNESSY;ZECHMEISTER;ZECHMEISTER, 2012;HULLEY et al., 2015). For data collection from secondary sources, scientific papers, books, and relevant organizational webpages on the subject were used, especially those that specifically bring a functional look and complementary details to the research practice. The screening process was based on the keywords: "survey", "research methods", "scales" and "questionnaire development." Further, we only includedstudies published between 2015 and 2020 that were available on the following platforms: Science Direct, Web of Science, SciELO, Google Scholar, Repositories, Institutional Database, and Google.
This study will present the planning for the most varied types of questionnaires, which will allow guiding the researcher to the best utilization protocol. Besides, suggestions on the planning and development of questionnaires were raised, predominantly basing on the authors' experience and the literature (which expresses the state-of-the-art in the investigated subject).
Finally, a hypothetical case is presented that demonstrates contexts relating to planning and developing questionnaires. Thus, comparative advancement is made possible by evaluating the technical formulation parameters and by guiding previous knowledge within the research process.

QUESTIONNAIRES AS INSTRUMENTS OF DATA COLLECTION
In clinical, educational, and organizational practice, most of the empirical research whose results are assessed through the analysis of primary data (raw data collected by the researcher) comes from the application of questionnaires (RATTRAY; JONES, 2007;HAIR et al. 2019). However, beyond the academic sphere, the robustness and validity of research results depend on the quality of the measurements.
The results of a survey may become invalid if the questionnaire has been improperly prepared. Since there are surveys that evaluate and describe characteristics of phe-nomena or attributes from participant perspectives, "for them to be useful, questionnaires must produce reliable and valid measures of demographic variables and individual differences on self-evaluation scales" (SHAUGHNESSY; ZECHMEISTER; ZECHMEISTER, 2012, p. 173).
As self-assessment scales, questionnaires are formally configured as re- CCEB uses a set of criteria that includes: (i) family income; (ii) comfort items (e.g., number of cars, TVs, rooms, etc.); (iii) education level of the head of the household (e.g., secondary school or higher education); or (iv) water supply (e.g., use of general distribution network). Here, the measurement approach is directly associated with the accuracy and precision of the analysis.
In addition to sociodemographic variables, questionnaires commonly seek to evaluate opinions (e.g., public surveys on the environment, food, etc.), intentions 6 (e.g., electoral research), beliefs, attitudes, and characteristics (e.g., marketing research, or psychological testing for clinical, organizational or academic purposes), among other aspects. Whatever the phenomenon to be evaluated is, collecting data in the real world and directly at the source is still the most effective way to access it, investigate it, draw safe conclusions, and make decisions (FIELD; HOLE, 2002).
Questionnaires, also called scales or self-assessment or self-reporting instruments, are tools with items (standardized questions) which are used to identify/map the judgment of an individual about a given phenomenon (e.g., everyday events or occurrences). They can also identify individual differences regarding some attribute or characteristic (e.g., leadership profile or job performance) in the form of a scale (SHAUGHNESSY; ZECHMEISTER; ZECHMEISTER, 2012).
Considering a hypothetical scenario, suppose that the human resources (HR) manager of a medium-sized company intends to investigate the reasons for low productivity among employees. To make an initial diagnosis, the HR manager decides to carry out an organizational climate survey and map different events of daily organizational life that vary in the dimensions of this construct (e.g., "leadership and organizational support", "pressure/control for results", and "cohesion among colleagues" -dimensions of the Organizational Climate Scale; for more details, see MARTINS, 2008).
In this scenario, the assessment focuses on the differences between the items of the aforementioned scale, and it is possible to infer which dimensions of the organizational climate may be negatively affecting productivity. In contrast, if the decrease in productivity has been identified in only one specific sector of the organization, it is possible to compare individuals according to the endorsement level on the organizational climate dimensions by identifying individual differences between sectors.
A questionnaire (instrument) capable of measuring organizational climate dimensions, for example, requires a meticulous compendium of techniques and criteria for its development, testing, validation, and standardization (consistency and objectivity of how tests are administered and scored). In our hypothetical scenario, for example, we may have the following problems: (1) Was the questionnaire developed based on a theory or at random? (2) Does the questionnaire use appropriate scaling, content, and semantics? (3) Was the questionnaire tested and corrected? 7 (4) Has the questionnaire been validated through psychometric and statistical procedures? (5) After the validation, were the scoring interpretation and standardization determined? In the case of Martins' instrument (2008), the answer is yes. However, for any questionnaire to be a discriminatory and qualified instrument to use in a survey, it must meet the same criteria.

QUESTIONNAIRE DEVELOPMENT PROCESS
Therefore, we recommend a questionnaire elaboration model that meets compatible and adaptable assumptions to the environmental and organizational circumstances of different types of research. We also consider psychometric aspects in order to enhance data captures with higher empirical quality. Initially, the theoretical procedures address the theory conception that underlies the questionnaire and specifies what will be measured and what is intended to be measured. Besides, the operationalization of these elements is approached on items or questions, based on aspects of semantic adjustment, relevance, and intelligibility. In addition, it should be analyzed by experts in the area (questionnaire theme) under investigation. As for the experimental procedures, the stages of sample definition, data collection, and questionnaire application are performed. In turn, the analytical procedures are related to the quality verification of the questionnaire, based on the analyses of validity and internal consistency, concluding in the elaboration of norms of scoring and interpretation (MALHOTRA, 2011;HAIR et al., 2014;PASQUALI, 2017).
This article does not deal with all these issues but, it points out the appropriate paths and references so that the required skills for planning, developing, and adapting questionnaires as valid and reliable self-assessment tools can be achieved. As Shaughnessy, Zechmeister, and Zechmeister (2012, p. 174) indicate, "the accuracy and precision of questionnaires as survey instruments depend on the knowledge and care involved in their construction".

PLANNING QUESTIONNAIRES
If applicable to empirical research, the questionnaire should be planned before and during the research project design, avoiding changes after the start of data collection. Thus, it is worth mentioning that the research project -i.e., the study or investigation conception -is the initial stage to identify the necessary key-elements for the planning and development of a questionnaire. Such key-elements are intrinsically related to the researchers' idea of the research itself.
Several handbooks of research methods have established a basic scope for the questionnaire development that shares a specific theoretical alignment (e.g.,   In an attempt to point out ways to clarify these methodological procedures and their practical meanings, the steps that provide the basis for planning a questionnaire are detailed respectively as follows: Based on the research problem: the research problem defines the object that the investigation will focus on, i.e., what will be measured/identified. In terms of questionnaire planning, understanding the research object is the same as determining, for example, whether the investigated phenomena are related to (i) individuals or (ii) processes. That allows us to establish the items' contents with greater accuracy in the questionnaire. In addition, a questionnaire with different aims is more complex to be understood by respondents and to be analyzed by researchers. When multiple aims are necessary, it is suggested to develop more than one questionnaire in order to guarantee the validity and consistency of each instrument.
Based on the research problem approach: the research problem approach defines the results presentation format that will be expected. In terms of questionnaire planning, one should think about the end of the research process and how the data analysis will be presented (e.g., texts, diagrams, figures, graphs, charts, or tables). On the one hand, if the researcher determines that the results will be presented through tables or graphs (i.e., elements to describe numerical variables), we recommend using closed items, which are commonly used in quantitative research. On the other hand, if the researcher decides to present the results through text or diagrams, open items are more appropriate (more frequent in qualitative research).
Based on the research-type specifications: the research-type specifications define the methodological objective of the questionnaire (to explore, describe, or explain a phenomenon). Generally, exploratory researches are more flexible than descriptive and causal researches. Therefore, for exploratory re-search, the elaboration of a new questionnaire seems more viable because the researchers can guide the research towards the thematic that they wish to deepen. In contrast, for descriptive and causal researches, specific analysis models are commonly used, which already have existing questionnaires with validity and reliability.
Nevertheless, if an investigation seeks to trace a cause and effect relationship (causal research), for example, between work motivation and productivity, a manager or consultant can use the Work Motivation Measure (QUEIROGA; BORGES-ANDRADE, 2015). However, they will need to develop their own questionnaire to measure work productivity in a specific context.

Based on the analysis procedures:
The analysis procedures objectively define the types of data that the research intends to collect. Each type of analysis requires different types of data, which directly implies the format of the items. For example, for an interpretative analysis of content, speech, or semantics, which share particular analytical methods and require textual data, open-ended questions are recommended in order to encourage respondents to express themselves freely. In contrast, a mean comparison analysis between two contrasting groups (e.g., average production between employees who have undergone training and employees who have not) requires the items to generate non-categorical numerical data that allow the use of mean statistics.
After designing these aspects, the researcher should "pay attention to the cost, the time, and to the structure to ensure an acceptable response rate for the study" (FREITAS et al., 2000, p. 107). Following this reasoning, Hair et al. (2014) ratify that the development of questionnaires is a logical and systematic process, which reflects the researchers' decisions on how data should be extracted (collection) and treated (analysis).

CONSTRUCT AND SCALING IN QUESTIONNAIRE DESIGN
As mentioned in the previous sections, questionnaires can assume different roles when conducting investigations. In surveys, for example, the questionnaire is characterized as the principal tool for analysing a phenomenon. Further, in re-12 searches for the development of measuring instruments and scales, the questionnaire itself is the main object of investigation. In other cases, the questionnaire can be a support tool when focused on the sample description (e.g., sociodemographic questionnaires). Therefore, different research applications require different types of questionnaires. Those types are commonly defined based on two elements: construct and scaling.
Conceptually, a construct is the characterization or definition of an object, aspect, attribute, characteristic, or phenomenon, which is composed and can be structured directly or indirectly by indicator elements. These indicator elements are essential properties that, when associated, explain a given construct (HAIR et al., 2014). For example, the quality of a product could be operationalized as a construct.
Customer perceptions and the technical characteristics of this product are indicative elements that together represent a concept: the quality. When developing a questionnaire, the definition of the construct to be analyzed determines the indicator elements (variables) that will be measured. In practical terms, it means establishing the context and content of the items.
In turn, scaling is the metric and standardized delineation of descriptors that represent the chaining and ordering of response options to items (i.e., indicator elements) of a given construct (HAIR et al., 2014). The descriptors determine the way the data will be extracted (collected), considering the most appropriate level of measurement for the type of scale: nominal, ordinal, interval, or ratio. Each level of measurement has requirements and content arrangement within a previously established structure. Proper scaling improves the possibilities of data analysis and increases the effectiveness of a questionnaire, especially regarding the reliability of the answers. According to Hair et al. (2014, p. 198), "whenever possible, it is preferable to use metric scales".
In a hypothetical scenario where managers aim to know the opinion of their employees about daily organizational procedures (a construct), we may evaluate individual perceptions by applying different measures (scaling). Those measures would depend on the nature of data, the survey functionality, or the available analysis options. In Table 2, we detail the levels of measurement and the analytical possibilities for each type of scaling. Likert-Type Scale Response options are standardized according to continuous intervals (e.g., 1 to 3, 1 to 5, 1 to 7, 1 to 9, or 1 to 11 points), generally odd ranges, between statements that express two extremes (e.g., from "1 -It doesn't describe me in absolute" to "7 -It describes me totally").

FORMULATION OF ITEMS (QUESTIONS) IN A QUESTIONNAIRE
Besides, the formulation of the items of a questionnaire represents an operational step linked to the chosen scaling as a measurement and analysis technique.
The literature warns that the items of a questionnaire should be planned considering their clarity, objectivity, and accuracy (e.g., MOREIRA, 2009;VIEIRA, 2009;GIL, 2019). Additionally, it is necessary to understand that the items are the nature of the questionnaire itself. Therefore, the questionnaire reflects the quality and extent of its items -its capability to collect data proficiently.
Aiming to establish minimum quality parameters for the items of a questionnaire, a compendium of 10 development and writing criteria is gathered in Table 3, which makes the questionnaire more robust.

Criteria Requirement
Unicity Each item must allow only one interpretation.

Objectivity
The item must be clear, precise and direct.

Simplicity
The item should express simple ideas, preferably one at a time.

Clarity
The item must be intelligible to the lowest stratum of the target population.

Relevance
The item must be consistent with the research and the proposed theoretical foundation.

Accuracy
The item must be precise and distinct from other items dealing with the same construct.

Variety
The items should vary in language, avoiding the use of the same terms.

Diligence
The items should avoid the use of extremist expressions.

Typicality
The items must use expressions and words that are related to the questionnaire theme.

Credibility
The item must be written in a way that it does not look ridiculous, unreasonable or childish.

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In addition to these criteria, the scaling and scope of the research project imply in the formulation of the items -besides interfering in the overall questionnaire planning. For scaling, it is necessary to understand that an item (e.g., one that investigates customers' opinions about a brand) may contain different response possibilities (see Table 2). Also, depending on the item format and its respective scaling (e.g., dichotomous, multiple-choice, or Likert scale), both analytical possibilities and data interpretation are modified.
Regarding the scope of the research project, it is suggested that the writing of the items follows the research method manuals (presented in the Questionnaire Planning section). Initially, the elements of investigation should be determined based on the research problem. For example, when the research focuses on people, it is possible to analyze individual characteristics (e.g., values or attitudes) or opinions (e.g., beliefs, satisfaction, or preferences). In contrast, when the investigation focuses on processes, it is possible to analyze the effectiveness or efficiency of a system, program, or procedure. The items should be adjusted in order to allow this measurement by considering the research content. Later, this will ensure that the data analysis will adhere to the research approach.
On the one hand, if the investigation elements (people or processes) are expressed numerically (e.g., size, extent, volume, or quantity) to meet the requirements of the research approach, a structured (closed) item should be prepared. From the initial scope of the structure of the items, we should determine how the data will be analyzed, based on the research type. For structured items, the quantitative bias predominates, which covers descriptive (e.g., frequency, mean, standard deviation), exploratory (e.g., correlation, factor analysis, multidimensional scaling), or confirmatory statistical analyses (e.g., linear regression, structural equations modeling). For unstructured items, the qualitative bias predominates, which covers procedures for interpreting observations or narratives from a specific point of view or perspective (ABDALLA et al., 2018). For example, content analysis (BARDIN, 2011) or computerized content analysis through Iramuteq (SOUZA et al., 2018).
Finally, after defining the structure of the items, the chosen analysis procedures should guide the types of data. This procedure may be related to the research purpose. Specifically, in a comparative quantitative research, the comparison of means is a viable procedure, whose type of analysis depends on the criterion vari- As shown in Table 2 For instance, the factor analysis identifies the items that retain the greatest power of explanation and suggests the withdrawal of those that do not present an explanatory contribution. The convergent-discriminating technique uses a hypothesis test to In turn, the precision should be interpreted as the reliability -also known as internal consistency or accuracy -of the questionnaire, representing the capability to measure an attribute consistently and considering the minimum of error (HAIR et al., 2014;PASQUALI, 2017;GIL, 2019). In most cases, the reliability of a questionnaire is estimated by employing Cronbach's alpha coefficient. It evaluates the inter- After the factor validity procedures, the authors presented an excessively large questionnaire with 81 items. In order to provide a questionnaire with a more parsimonious and accurate set of items, the authors choose the 40 items with the best explanation power (i.e., items with the highest factor loadings). Additionally, Souza et al. (2016) estimated the reliability of the IBFE through Cronbach's alpha -a measure that varies from 0.0 to 1.0, being the value of 0.600 considered the lower limit of acceptability (HAIR et al., 2018). Therefore, the IBFE demonstrated factor validity and internal consistency.
Next, to assess criterion validity, the authors assumed the hypothesis that entrepreneurs presented more facilitators to entrepreneurship than university students.
The means of entrepreneurs (n = 57) were compared to the means of university students (n = 194) through the Student t-test. The results confirmed the hypothesis and indicated the questionnaire's precision (SOUZA et al., 2016).
However, obtaining a valid and precise questionnaire involves theoretical knowledge, analytical skills, experience with data collection procedures, and advanced statistical analysis skills (HAIR et al., 2018;PASQUALI, 2017). Because of this, Field and Hole (2002) emphasize that the essential golden rule, for any type of research, is to avoid developing the own questionnaire and invest in ready-to-use instruments, in which adequate validity and reliability parameters have already been checked.

READY-TO-USE QUESTIONNAIRES (RESEARCH INSTRUMENTS)
When conducting a research project, developing a questionnaire and, consequently, utilizing it is a challenging task. Usually, the development of a questionnaire is the research project itself, given the involved level of complexity, the required enormous time, and the lack of guarantee that, in the end, the developed questionnaire will be useful for the researcher.
Well-designed, theoretically grounded, and highly functional questionnaires require years to develop and confirm their validity. To be properly calibrated and obtain its standardization, a questionnaire may take decades to be completed like As a result, some authors (e.g., FIELD; HOLE, 2002; PASQUALI, 2017) advocate the use of existing instruments (with assessed validity and reliability parameters) in research projects, whose technical and theoretical quality has been empirically tested to determine a more precise data accuracy and gain methodological robustness.
Most useful questionnaires for research in business administration are found in scientific-academic journals, dissertations/theses, and books. For example, the  (LAROS et al., 2018). Table 4 shows examples of books and websites that provide questionnaires and research instruments with validity and reliability. Those questionnaires are ready-to-use for researching in business administration, and they provide precision, adjustment, and standardization.

QUESTIONNAIRE STRUCTURE PLANNING
In the absence of ready-to-use questionnaire options, researchers may need to develop their own questionnaire with specific items and content to the research demands. Most research methods manuals are consensual on the need for an exhaustive literature review on all the theoretical and empirical elements associated with the questionnaire theme.
As mentioned previously, research manuals guide the questionnaire development according to the research project fundamentals, which precede the questionnaire development and justify its elaboration. In particular, those manuals establish that the development of a questionnaire should be a rigorous and detailed process.
This process comprises the production and revision of items (either in content or semantics), scaling, and application structure, aiming at establishing advanced data collection practices.
Therefore, the checklist below explains elementary procedures for the devel-  2. After that, the information and data to be collected should be listed, considering the alignment with the central objective of the research.
3. Afterwards, one should determine the requirements for the data collection 4. The items should be written according to the criteria indicated in Table 1. 11. At the end of the questionnaire, it is suggested to thank the respondents.
12. Once the questionnaire is ready, an introductory section should be written to include a general description of the study.
13. After the introductory section, the questionnaire should present an informed consent form, and the researchers should be aware of ethical is- 14. Finally, the format and layout of the questionnaire should be determined for a pretest phase.

Illustration of a Hypothetical Case
In order to demonstrate the practical aspects of planning and developing questionnaires, an illustration of a hypothetical case in a managerial context is presented below.
This hypothetical context comprises a medium-sized retail company (clothing business) subdivided into the administrative sector (e.g., salary payment and materials management), the financial sector (e.g., financial transaction flow and accounting), and the commercial sector (e.g., customer registration, sales prospecting, and after-sales). Also consider that this company needs to implement a management information system (MIS).
Sectorial managers observed problems such as: (i) operational failures, (ii) reports with inaccurate information, (iii) supplier invoices with incorrect payment, (iv) difficulty in product exchange, among others. Therefore, the use of an integrated MIS was proposed. After its conception, the integrated MIS had the following mod- 26 ogy in daily work]. Since the managers wanted to focus on perceptions mapping about the implemented system, and the questionnaire should be related to user satisfaction, the first questionnaire was unsuitable for the research proposal. Then, the managers looked for a questionnaire closer to the desired context and found the instrument of Harrati et al. (2016), which is about end-user satisfaction regarding computational tools.
Nevertheless, the questionnaire did not meet all the research requirements.
When the objective is to map or evaluate the impact of specific actions on individuals, a team, or an organization -as in this illustrative case -with direct reflexes on the production line, it is likely that the development of a specific questionnaire will also be necessary.
Therefore, the managers decided to develop a new questionnaire by following the steps from the research methods manuals and considering the notes from the Questionnaire Planning section in this article. Before starting the development of the questionnaire, the managers responded to four basic questions: (1) What will be investigated? (2) What will the type of questionnaire be like? (3) How will the data be analyzed? (4) What type of data will be collected? The managers answered these questions as follows: (1) people; (2) structured (closed) questionnaire by a quantitative approach; (3) statistic of mean to perform tests of correlation and comparison of means; (4) ordinal/interval data.
Based on those answers, they obtained a more explicit direction to start the questionnaire developing process. In conclusion, the managers created specific items for the investigation by following the instructions in Table 1, and proceeded to the operational phases of diagramming, designing, validating, and testing the questionnaire.

Final Remarks
This article aimed to deepen the planning and operationalization of questionnaires as research tools, considering theoretical and practical perspectives. In this manner, it intertwines the knowledge in psychometry (scaling, measurement theory, validity, and reliability) with marketing research (surveys and projects con-duction), and focuses on best practices in empirical research through the use of questionnaires.
The use of validated and standardized ready-to-use questionnaires is highlighted and defended in this article, as they provide an effective means for measurements with quality and effectiveness, translating into more reliable data and more accurate results. Nevertheless, given the necessity of developing a questionnaire, we recommended reflecting on the research or investigation to be undertaken. Planning questionnaires should start from the definition of the measure and the scaling.
A valid and precise questionnaire meets data requirements and research objectives.
Also, the data collection without adequate theoretical and experimental treatment leads to measurement errors and high bias rates (beyond those already existing in any investigation through self-reported questionnaires).
As a limitation, this study does not address all elements for the development of questionnaires since only one article does not account for all textual and graphic elements available. For example, we do not deepen validity and reliability aspects because there is a vast literature that deals with related psychometric and statistical details (e.g., HAIR et al., 2018;PASQUALI, 2017;CALLEJA et al., 2019).
Also, we do not deepen the data collection steps since specific literature in marketing research develops this topic proficiently (e.g., MALHOTRA, 2011;HAIR et al., 2014;MALHOTRA, 2018). Besides, this study does not bring contributions to the adaptation of already validated and ready-to-use questionnaires in a specific research context. This adaptation process may involve translation, terminology changes, and other operational modifications that require particular procedures, as if developing a new instrument. For details on questionnaire adaptation, see Phongphanngam and Lach (2019).
Ultimately, for more considerable proficiency in planning, development, validation, and standardization of questionnaires, the experience of the researcher in this activity is essential, including knowledge in data processing and analysis (quantitative or qualitative),and the expanded use of quality research instruments already validated.