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2023 | OriginalPaper | Chapter

14. Research Findings

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Abstract

This chapter details the sample selection, data check and cleansing as well as manipulation check, realism check and the research methodology.

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Appendix
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Footnotes
1
In accordance with KROSNICK/PRESSER (2010) and previous studies such as SINNIG (2019), HIDDESSEN (2020), LIENEMANN (2021) and DIEGEL (2021) respondents had the option of selecting “I don’t know” for all questions, with the exceptions of the screening and realism questions. Cf. KROSNICK/PRESSER (2010), p. 263; SINNIG (2019), p. 126; HIDDESSEN (2020), p. 119, LIENEMANN (2021), p. 119; DIEGEL (2021), p. 176.
 
2
It is recommended to exclude all cases that have more than 30% missing values Cf. WIRTZ (2004), p. 110 et seq.; SINNIG (2019), p. 126; LIENEMANN (2021), p. 119.
 
3
Cf. VOORHIS/MORGAN (2007), state that 30 participants per group should result in approximately 80% power, which is the minimum suggested power for a typical study. Furthermore, it is paramount to have more groups than dependent variables in the experiment. VOORHIS/MORGAN (2007), p. 48.
 
4
Cf. ZIKMUND/BABIN (2010), p. 163.
 
5
Cf. ZIKMUND/BABIN (2010), p. 271.
 
6
By focusing on a sample that goes beyond student respondents, we act in accordance with ASHRAF/MERUNKA (2017). Cf. ASHRAF/MERUNKA (2017), p. 295.
 
7
Cf. KOCH/PETER/MÜLLER (2019), p. 85.
 
8
Cf. KLEIN/BECKER (2018), p. 5.
 
9
Cf. EVANS ET AL. (2017), p. 143; DE VEIRMAN/HUDDERS (2020), p. 31. BOERMAN/VAN REIJMERSDAL/NEIJENS (2012), p. 1054 similarly employs this operationalization for brand memory.
 
10
Cf. KARANDE/MAGNINI/TAM (2007), p. 192.
 
11
Cf. SHAMON/BERNING (2020), p. 56.
 
12
Cf. SHAMON/BERNING (2020), p. 56.
 
13
Cf. BOERMAN (2012), p. 1050; VAN REIJMERSDAL ET AL. (2017), p. 338.
 
14
HAYES (2017), p. 1.
 
15
The PROCESS Macro is applicable for SPSS, SAS and R. Cf. HAYES (2017), p. 82.
 
16
Cf. HAYES (2022), p. 1; BREAUGH (2006), pp. 429 et seq.
 
17
Cf. HAYES (2017), p. 6.
 
18
Cf. HAYES (2022), p. 1; HAYES (2022), p. 7.
 
19
Cf. VAN REIJMERSDAL ET AL. (2017), p. 335. The authors use Hayes model 4, but cannot support the hypothesis (N = 221).
 
20
Cf. BOERMAN (2020) uses Hayes PROCESS macro model 4 for SPSS. Thus, he can support that standard Instagram disclosure increases ad recognition, which in turn lessens respondents’ behavioural intentions, when compared to no disclosure (N = 192). Cf. BOERMAN (2020), p. 204.
 
21
Cf. BECKERT ET AL. (2020) use the standard model 4, that includes only mediators, and no moderators, which is appropriate for their hypotheses. They are able to support that the independent variable sponsorship disclosure has a negative effect on the dependent variable anger via two parallel mediators namely, persuasive and deceptive intent. This observation has been supported for the Instagram environment (N = 125) and the blog environment (N = 238), but not for the online newspaper environment (N = 81). Cf. BECKERT ET AL. (2020), p. 10.
 
22
Cf. BREVES ET AL. (2021) Support that due to higher degrees of parasocial relationships (mediator 1), followers (independent variable) will observe higher perceived source credibility (mediator 2) than non-followers. Similarly, they could support that followers will assess sponsored posts (dependent variable) more positively than non-followers. (N = 157). Cf. BREVES ET AL. (2021), p. 7.
 
23
Cf. KLEIN/BECKER (2018), p. 6. While the authors cannot support the above-mentioned proposition for source credibility, the authors can support that MPE diminishes trustworthiness which in turn reduces purchase intention, when observed for macro SMIs (N = 1.238). Cf. KLEIN/BECKER (2018), p. 8.
 
24
Cf. STUBB/COLLIANDER (2019b) could only support “landing page content” moderating the effect of disclosure type on the dependent variable brand attitude but not on the dependent variable purchase intention. The authors employed Hayes PEOCESS model 1 (N = 375). Cf. STUBB/COLLIANDER (2019b), p. 218.
 
25
Cf. DE VEIRMAN/HUDDERS (2020) support that the moderator “message one snideness” (a very positive message, enumerating only the advantages and not the disadvantages of a product) leads to a higher occurrence of the indirect negative effect of sponsorship disclosure on brand attitude, via the mediator perceived credibility (N = 355). Cf. DE VEIRMAN/HUDDERS (2020), p. 107.
 
26
Cf. STEILS/MARTIN/TOTI (2022) analyze in their first study N = 181 Instagram post that contain a #brandhashtag. The author can support that only for the cases of Maro- or Mega-SMIs, disclosure messages were beneficial and increased consumer engagement. Cf. STEILS/MARTIN/TOTI (2022), p. 154.
 
27
Cf. HAYES (2017), p. VIII (preface).
 
28
Cf. HAYES (2017), p. 8.
 
29
Cf. HAYES (2017), p. 9.
 
30
Cf. HAYES (2013), p. 3; HAYES (2017), p. 612.
 
31
Cf. REGORZ (2019).
 
32
Cf. HAYES (2017), p. 608.
 
33
Cf. HAYES (2017), p. 562. We were also able to add a bmatrix (conditional process model matrix) and a wmatrix (moderator matrix). Cf. HAYES (2017), pp. 557 et seq.
 
34
Cf. BECKER (2005), pp. 274 et seq. Th authors analyze 60 empirical articles published during 2000 to 2002. Cf. KLARMANN/ FEURER (2018), p. 34.
 
35
Cf. ATINC/SIMMERING (2008); BECKER (2005), p. 302.
 
36
Cf. ATINC/SIMMERING/KROLL (2012), p. 57. The authors review 812 empirical articles published during 2005 to 2009. Their findings highlight that only 48% of articles provided a theoretical reason for control variable inclusion. Cf. ATINC/SIMMERING/KROLL (2012), p. 65.
 
37
SPECTOR/BRANNICK (2010), p. 289.
 
38
Cf. KOSCHATE (2008) p. 109; BOERMAN/VAN REIJMERSDAL/NEIJENS (2012), p. 1054; MCDANIEL/GATES (2013), p. 242; NEE (2016), p. 110; SINNIG (2019), p. 96; DIEGEL (2021), p. 147; ANDRADE (2021), p. 178.
 
39
Cf. TROMMSDORFF (2009), p. 147; KROEBER-RIEL/WEINBERG/GRÖPPEL-KLEIN (2009), pp. 224 et seqq.; SCHADE (2012), p. 34; BURMANN/HALASZOVICH/SCHADE/PIEHLER (2018), p. 16.
 
40
Cf. BURMANN/STOLLE (2007), p. 23.
 
41
Cf. MITCHELL/OLSON (1981), p. 323; ABRAHAM (2020), p. 114; LIENEMANN (2021), p. 111.
 
42
Cf. MITCHELL/OLSON (1981), p. 326.
 
43
Cf. DE VEIRMAN/HUDDERS (2020), p. 118; SIMONIN/RUTH (1998), p. 39 also underline the spillover effects of brand familiarity.
 
44
Cf. HONG/STERNTHAL (2010), p. 301. Especially when the participants prior knowledge and the message concerning the brand fit with each other, brand evaluation tend to be more favorable. As this would be the case, we successfully avoided this distortion by choosing a brand that is not widely known in Germany.
 
45
Cf. SIMONIN/RUTH (1998), p. 39; CHOI/RIFON (2012), p. 644; SINNIG (2019), p. 114.
 
46
Cf. SUNDARAM/WEBSTER (1999), pp. 665 et seq. supports that brand familiarity will moderate brand evaluations as well as purchase intentions and brand attitudes positively. Thus, familiar brands receive more favorable evaluations when compared to unfamiliar brands. This is in accordance with STEILS/MARTIN/TOTI (2022), p. 8, who also choose an unknown brand for the French market. Similarly, the authors underline that widely known brands bring on consumer bias which is based on previous experiences with the brand.
 
47
Cf. STEILS/MARTIN/TOTI (2022), p. 8.
 
48
Cf. HWANG/JEONG (2016), p. 531, VAN REIJMERSDAL ET AL. (2017), p. 335; ABDULLAHI (2020), p. 14; DE CICCO/IACOBUCCI/PAGLIARO (2020), p. 15; KARAGÜR/BECKER/ KLEIN/EDELING (2021), p. 30.
 
49
Cf. KARAGÜR/BECKER/KLEIN/EDELING (2021), p. 30.
 
50
Cf. HAYES (2017), p. 14.
 
51
Cf. STATISTICSSOLUTIONS (2022).
 
52
Cf. AKINWANDE/DIKKO/AGBOOLA (2015), p. 755.
 
53
Cf. AKINWANDE/DIKKO/AGBOOLA (2015), p. 756.
 
54
Cf. MOORE/NOTZ/FLINGER (2013), p. 105; LIBGUIDES (2022).
 
55
Cf. SPECTOR/BRANNICK (2010), p. 297.
 
56
Cf. HAYES (2017), p. 14.
 
57
The introduction of the control variable “Likeability” (even in a limited manner, with “purchase intention” as a dependent variable) reverses the positive effect of credibility on purchase intention shown in the model without control variables, to a negative effect. Thus, the addition of “Likeability” invalidates H3.
 
58
The model calculated without control variables shows a significant negative effect between ad perception and credibility. The introduction of “Global image” or “Brand Familiarity” even with the dependent variable being only purchase intention, renders the effect between ad perception and credibility as not significant.
 
59
Cf. ARAH (2008), p. 1.
 
60
Cf. LUDLOW/KLEIN (2014), p. 3.
 
61
Cf. BERNERTH ET AL. (2018), p. 132; BREAUGH (2006), p. 429.
 
62
Cf. ATINC/SIMMERING/KROLL (2012), p. 57. The authors review 812 empirical articles published during 2005 to 2009. Their findings highlight that only 48% of articles provided a theoretical reason for control variable inclusion. Cf. ATINC/SIMMERING/KROLL (2012), p. 65.
 
63
SPECTOR/BRANNICK (2010), p. 289.
 
64
Cf. SPECTOR/BRANNICK (2011), p. 288; BERNERTH ET AL. (2018), p. 132.
 
65
Cf. ATINC/SIMMERING/KROLL (2012), p. 59; BERNERTH ET AL. (2018), p. 132.
 
66
Cf. BERNERTH ET AL. (2018), p. 132.
 
67
Cf. BERNERTH ET AL. (2018), p. 132; BREAUGH (2006), p. 429; EDWARDS (2008), pp. 469 et seq.
 
68
In this case literature calls this the product of a “suppression effect”. This effect means that when predictor variables correlate, the outcome will change with each addition of the predictor. A suppressor is an independent variable, with a part correlation, larger than zero-order correlation, with the dependent variable. Cf. MACKINNON/KRULL/LOCKWOOD (2000), p. 175; ATINC/SIMMERING/KROLL (2012), p. 71; BERNERTH ET AL. (2018), p. 132.
 
69
Cf. SPECTOR/BRANNICK (2011), p. 294.
 
70
Cf. KLARMANN/FEURER (2018), p. 37.
 
71
Cf. OHANIAN (1990), p. 41.
 
72
The variance of the dependent variable is represented by the R2-value, which is obtained by squaring the correlation coefficient. It depicts the total variance percentage of the dependent variable’s (Y), that can be explained by changes in the independent variable (X). ZIKMUND/BABIN (2010), p. 595.
 
73
Cf. HAYES (2017), p. 14.
 
74
Cf. HWANG/JEONG (2016), p. 533.
 
75
Cf. HWANG/JEONG (2016), p. 530.
 
76
Cf. STUBB ET AL. (2019a), p. 111.
 
77
Cf. CARR/HAYES (2014), p. 43.
 
78
Cf. HWANG/JEONG (2016), p. 531.
 
79
Cf. STUBB/COLLIANDER (2019b), p. 218.
 
80
Cf. HAYES (2017), p. 14.
 
81
Cf. OHANIAN (1990), p. 41.
 
82
Cf. CARR/HAYES (2014), p. 43.
 
83
Cf. HWANG/JEONG (2016), p. 531.
 
84
Cf. STUBB/COLLIANDER (2019b), p. 218.
 
85
Cf. HAYES (2017), p. 14.
 
86
Cf. OHANIAN (1990), p. 41.
 
87
Cf. CHU/KAMAL (2008), p. 32.
 
88
Cf. TATAGE (2017), p. 37.
 
89
Cf. SOKOLOVA/KEFI (2019), p. 10.
 
90
Cf. DE JANS/CAUBERGHE/HUDDERS (2018), p. 11.
 
91
Cf. THIEFES (2021), p. 185.
 
92
Cf. HAYES (2017), p. 14.
 
93
Cf. KIM/KIM (2020), p. 3.
 
94
Cf. HAYES (2017), p. 14.
 
95
Cf. OHANIAN (1990), p. 41.
 
96
Cf. MARTINEZ-LOPEZ ET AL. (2020), p. 1817.
 
97
Cf. OHANIAN (1990), p. 41.
 
98
As this relation includes two mediators, it is a serial mediation. Cf. HAYES (2017), pp. 167 et seqq.
 
99
Cf. HAYES (2017), p. 14.
 
100
Cf. OHANIAN (1990), p. 41.
 
101
Cf. HAYES (2017), pp. 219, et seqq.:
 
102
Cf. OHANIAN (1990), p. 41.
 
103
Cf. HAYES (2017), p. 14.
 
104
Cf. OHANIAN (1990), p. 41.
 
105
Cf. HAYES (2017), pp. 219, et seqq.
 
106
Cf. OHANIAN (1990), p. 41.
 
107
Cf. HAYES (2017), p. 14.
 
108
Cf. HAYES (2017), p. 14.
 
109
Cf. KI ET AL. (2020), p. 1.
 
110
Cf. SÁNCHEZ-FERNÁNDEZ/JIMÉNEZ-CASTILLO (2021), p. 1124.
 
111
Cf. LIENEMANN (2021), p. 118.
 
Metadata
Title
Research Findings
Author
Corina Oprea
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-658-41364-4_14

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