宋瑩 阮勝坤
摘要: 隨著消費(fèi)者著裝需求個(gè)性化要求的提高,在服裝設(shè)計(jì)過程中只有充分考慮到用戶的感性需求,才能設(shè)計(jì)出符合消費(fèi)者滿意度的服裝產(chǎn)品。本文以男襯衫為研究對(duì)象,提出感性工學(xué)與數(shù)量化理論Ⅰ相結(jié)合的款式設(shè)計(jì)研究方案。首先通過語意差異法獲取消費(fèi)者對(duì)男襯衫樣本的感性評(píng)價(jià),再利用SPSS軟件對(duì)評(píng)價(jià)結(jié)果進(jìn)行分析,提取感性因子,從而創(chuàng)建男襯衫二維感性分布空間。同時(shí)分析款式特征,歸納出男襯衫主要設(shè)計(jì)要素,在此基礎(chǔ)上應(yīng)用數(shù)量化理論Ⅰ,通過線性回歸分析得出感性因子與設(shè)計(jì)要素之間的關(guān)聯(lián)預(yù)測,并構(gòu)建數(shù)學(xué)模型。經(jīng)驗(yàn)證,該模型實(shí)測值與預(yù)測值之間擬合度較高,符合正態(tài)分布要求,模型有效可行。最后通過案例設(shè)計(jì)與驗(yàn)證,進(jìn)一步證明該模型能夠?qū)崿F(xiàn)用戶感性需求與男襯衫設(shè)計(jì)要素之間的有效轉(zhuǎn)換,對(duì)男襯衫款式設(shè)計(jì)與感性評(píng)價(jià)具有一定借鑒作用。
關(guān)鍵詞: 男襯衫;感性工學(xué);款式設(shè)計(jì);數(shù)量化理論;設(shè)計(jì)要素;數(shù)學(xué)模型
中圖分類號(hào): TS941.26
文獻(xiàn)標(biāo)志碼: A
文章編號(hào): 1001-7003(2023)03-0105-08
引用頁碼:
031202
DOI: 10.3969/j.issn.1001-7003.2023.03.014(篇序)
隨著服裝產(chǎn)業(yè)日益激烈的市場競爭,傳統(tǒng)、單一同質(zhì)化的服裝款式,已經(jīng)遠(yuǎn)不能滿足消費(fèi)者對(duì)著裝個(gè)性化與多樣化的心理消費(fèi)需求。人們通過著裝追求情感的愉悅與個(gè)性的展示,因此以消費(fèi)者為中心的服裝設(shè)計(jì)理念愈發(fā)受到重視[1],他們對(duì)服裝款式造型的感性評(píng)價(jià)也成為影響其消費(fèi)行為的重要因素之一[2]。
感性工學(xué)(Kansei engineering)的概念由日本著名設(shè)計(jì)學(xué)大師山本健一提出[3],主要用于將無法或難以量化的主觀因素進(jìn)行客觀量化[4],并對(duì)量化結(jié)果與產(chǎn)品設(shè)計(jì)要素之間關(guān)系進(jìn)行明確探討[5],幫助設(shè)計(jì)師設(shè)計(jì)出更貼合“人”的感性需求的產(chǎn)品[6]。目前這一理論已經(jīng)在服裝設(shè)計(jì)、汽車制造等多個(gè)領(lǐng)域得到廣泛應(yīng)用。例如,Jin等[7]以消費(fèi)者特定文化背景情感下的感性需求為研究對(duì)象,對(duì)消費(fèi)者對(duì)時(shí)尚設(shè)計(jì)的情感反應(yīng)進(jìn)行感性評(píng)價(jià),將消費(fèi)者的感性需求量化為概念框架,進(jìn)而為時(shí)尚設(shè)計(jì)提供一定的理論指導(dǎo)。Ge等[8]針對(duì)男士純色襯衫的網(wǎng)購銷量逐漸下降的現(xiàn)象,利用感性工學(xué)對(duì)如何解決這一問題進(jìn)行分析,發(fā)現(xiàn)網(wǎng)上銷售標(biāo)題中關(guān)于造型和色彩的描述最能吸引消費(fèi)者,進(jìn)而總結(jié)出如何通過提高純色男襯衫網(wǎng)上銷售標(biāo)題的質(zhì)量來提高其點(diǎn)擊量和成交量。Chen等[9]利用感性工程理論和方法獲取用戶的感知圖像,并基于形態(tài)分析方法對(duì)圖案進(jìn)行解構(gòu)和編碼找到相應(yīng)的設(shè)計(jì)代碼組合,最后以服裝剪紙圖案為例進(jìn)行驗(yàn)證;驗(yàn)證結(jié)果表明,該設(shè)計(jì)系統(tǒng)在圖案設(shè)計(jì)中能很好地反映用戶的感性形象,提高圖案定制服務(wù)的效率。
在產(chǎn)品設(shè)計(jì)的過程中,著重凝練消費(fèi)者的感性需求,能夠更好地實(shí)現(xiàn)設(shè)計(jì)目的,避免產(chǎn)品同質(zhì)化現(xiàn)象的發(fā)生。數(shù)量化理論Ⅰ(Quantitation theory Ⅰ)作為研究人類主觀感性需求與產(chǎn)品設(shè)計(jì)要素相關(guān)性的主要方法之一[10],通過創(chuàng)建多元回歸數(shù)學(xué)模型對(duì)因變量的變化趨勢(shì)與特征進(jìn)行預(yù)測,并歸納出因變量與自變量之間的相互關(guān)聯(lián)規(guī)律[11]。在此基礎(chǔ)上,利用所獲取的參數(shù)將主客觀2種不同性質(zhì)的變量進(jìn)行科學(xué)整合,最終實(shí)現(xiàn)產(chǎn)品設(shè)計(jì)要素與“人”的感性需求之間的有效融合,幫助設(shè)計(jì)師設(shè)計(jì)研發(fā)出更能滿足消費(fèi)者心理需求的產(chǎn)品[12]。目前,該理論在服裝設(shè)計(jì)領(lǐng)域主要應(yīng)用在消費(fèi)者感性需求與服裝款式設(shè)計(jì)要素對(duì)應(yīng)關(guān)系的研究中[13],且已有學(xué)者在對(duì)服裝造型、面料及色彩等設(shè)計(jì)要素進(jìn)行主觀研究的基礎(chǔ)上,結(jié)合數(shù)量化理論Ⅰ對(duì)服裝設(shè)計(jì)原理與規(guī)則進(jìn)行量化總結(jié)與歸納[14]。
通過對(duì)現(xiàn)有文獻(xiàn)的研究可知,目前大多數(shù)利用感性工學(xué)進(jìn)行服裝款式設(shè)計(jì)的研究,更多是集中在服裝單一部件與某一細(xì)節(jié)方面,缺少對(duì)某一類服裝整體款式造型的研究,同時(shí)也缺乏對(duì)研究結(jié)論的客觀驗(yàn)證。針對(duì)這一現(xiàn)狀,本文以男襯衫為研究對(duì)象,總結(jié)提取其款式設(shè)計(jì)的主要要素,根據(jù)選取的男襯衫款式圖,采用語意差異法對(duì)感性詞對(duì)進(jìn)行評(píng)分;在此基礎(chǔ)上,將數(shù)量化理論Ⅰ與感性工學(xué)相結(jié)合,深入探討消費(fèi)者感性需求與男襯衫款式設(shè)計(jì)要素之間的關(guān)聯(lián)度,并建立與之對(duì)應(yīng)的回歸預(yù)測模型,進(jìn)而為設(shè)計(jì)師設(shè)計(jì)出具有較高市場滿意度的男襯衫提供參考與建議。
1 感性工學(xué)研究
本文感性工學(xué)研究首先通過收集并確定男襯衫研究樣本、提取款式設(shè)計(jì)要素、確定感性詞對(duì),在此基礎(chǔ)上創(chuàng)建感性調(diào)研問卷,通過被調(diào)者對(duì)男襯衫樣本的感性評(píng)分建立消費(fèi)者的感性需求與男襯衫之間的關(guān)聯(lián)性;利用SPSS 26.0軟件對(duì)問卷結(jié)果進(jìn)行相關(guān)性分析,最終確立男襯衫款式造型與感性意象之間的關(guān)聯(lián)度。具體研究流程如圖1所示。
1.1 確定研究樣本
由于男襯衫款式造型變化主要體現(xiàn)在衣身部分,袖子長度對(duì)襯衫整體造型風(fēng)格影響不大[15],因此本文將男襯衫統(tǒng)一為春秋季長袖男襯衫。
通過查閱服裝雜志、訪問服裝設(shè)計(jì)類網(wǎng)站及走訪實(shí)體店面等形式,對(duì)男襯衫款式圖片進(jìn)行收集,由10名服裝設(shè)計(jì)領(lǐng)域?qū)I(yè)人士與10名高校服裝設(shè)計(jì)專業(yè)教師,從中篩選出20款具有代表性的男襯衫款式圖片作為研究樣本。同時(shí)為了保證對(duì)男襯衫款式造型的后續(xù)評(píng)價(jià)不受面料質(zhì)地、圖案、顏色、配飾及模特等因素的干擾,利用Adobe Illustrator artwork 22.0將研究樣本繪制成比例一致的黑白線圖,作為后續(xù)研究的刺激圖(圖2)。將款式造型接近的男襯衫刺激圖分開排列,以免觀察者混淆。
1.2 設(shè)計(jì)要素提取
男襯衫在款式設(shè)計(jì)上主要包括整體廓形和細(xì)節(jié)造型的設(shè)計(jì)。本文對(duì)收集的男襯衫款式造型進(jìn)行分析,在此基礎(chǔ)上將男襯衫款式設(shè)計(jì)要素提煉為8個(gè)要素,以及23個(gè)要素子類目,如表1所示。
其中廓形要素中,將貼近人體、放松量較小、凸顯腰線的款式造型定義為修身;將與人體距離適中、放松量適中,且胸圍與腰線呈直線造型的款式造型定義為合身;將襯衫遠(yuǎn)離人體、整體尺寸放松量較大,且肩線下落明顯的款式造型定義為寬松。
1.2.1 確定感性詞對(duì)
通過閱讀服裝專業(yè)書籍、雜志,廣泛收集對(duì)服裝風(fēng)格進(jìn)行感性描繪的形容詞,首次整理出80個(gè)與男襯衫造型風(fēng)格相關(guān)的感性形容詞,對(duì)意思相近的詞匯進(jìn)行提煉,并剔除低頻形容詞;最后邀請(qǐng)10名專業(yè)的服裝設(shè)計(jì)人員最終確定出最能準(zhǔn)確描述男襯衫造型,且出現(xiàn)頻率最高的8對(duì)具有相反語意的形容詞對(duì)作為本次研究的感性詞對(duì)。8對(duì)感性詞對(duì)分別為:老氣的—年輕的、正式的—休閑的、簡單的—復(fù)雜的、大眾的—個(gè)性的、經(jīng)典的—時(shí)尚的。穩(wěn)重的—活潑的、儒雅的—粗獷的、保守的—前衛(wèi)的。
1.2.2 調(diào)查問卷設(shè)計(jì)
本問卷采用5個(gè)感覺量級(jí)的產(chǎn)品語意差異法對(duì)調(diào)查問卷進(jìn)行設(shè)計(jì)[16],讓受調(diào)者對(duì)男襯衫樣本的款式與8對(duì)感性詞對(duì)之間的吻合程度通過賦分的形式進(jìn)行評(píng)價(jià)。問卷中的分值代表20款男襯衫樣本與感性詞對(duì)相對(duì)應(yīng)的關(guān)聯(lián)度,分別為-2、-1、0、1和2。以形容詞對(duì)“正式的—休閑的”為例,-2表示該款男襯衫給人的感性印象特別正式、-1表示比較正式、0表示該款男襯衫既談不上正式也談不上休閑、1表示比較休閑、2表示特別休閑。
2 研究結(jié)論分析
2.1 數(shù)據(jù)統(tǒng)計(jì)
本調(diào)查問卷的調(diào)研對(duì)象為服裝設(shè)計(jì)專業(yè)高校教師、學(xué)生及服裝公司專業(yè)設(shè)計(jì)人員,利用問卷星的形式通過網(wǎng)絡(luò)平臺(tái)進(jìn)行發(fā)放,共發(fā)放問卷110份,回收有效問卷106份,回收率96.4%,符合調(diào)查問卷樣本的容量要求。計(jì)算出有效問卷中20款樣本的感性評(píng)分的平均值,將0作為評(píng)價(jià)的分界點(diǎn),所得評(píng)價(jià)分值距離0分越遠(yuǎn),表示其與對(duì)應(yīng)方向的感性詞的關(guān)聯(lián)度越高。
采用SPSS 26.0軟件對(duì)評(píng)價(jià)結(jié)果的平均值進(jìn)行KMO效度分析及Bartlett球形檢驗(yàn),將感性詞對(duì)設(shè)置為變量,具體檢驗(yàn)結(jié)果如表2所示。表2中,KMO效度分析值為0.832>0.5,Bartlett球形檢驗(yàn)顯著性P值為0.000<0.05,說明各變量之間存在顯著的相關(guān)性,符合因子分析[17]條件。
2.2 數(shù)據(jù)分析
2.2.1 因子分析
采用主成分分析法對(duì)因子分析中的公因子進(jìn)行提取,得出感性形容詞對(duì)的解釋總方差,如表3所示。通過表3可以看出,所提取出的2個(gè)成分的累積貢獻(xiàn)率為84.747%,對(duì)原有因子解釋損失較少。進(jìn)而說明選擇2個(gè)因子能夠表達(dá)所有形容詞對(duì)的大多數(shù)信息,可以對(duì)20款男襯衫樣本的款式造型進(jìn)行有效的感性心理評(píng)價(jià)。
采用最大方差法通過正交旋轉(zhuǎn)得出各因子的載荷矩陣,如表4所示。由表4可看出,儒雅的—粗獷的、穩(wěn)重的—活潑的、正式的—休閑的和老氣的—年輕的這4對(duì)感性詞對(duì),在因子1上具有較高載荷,并根據(jù)感性詞對(duì)變量的具體含義將其命名為“氣質(zhì)因子”(F1);經(jīng)典的—時(shí)尚的、簡單的—復(fù)雜的、保守的—前衛(wèi)的和大眾的—個(gè)性的這4對(duì)感性詞對(duì),在因子2上具有較高載荷,并根據(jù)感性詞對(duì)變量的具體含義將其命名為“潮流因子”(F2)。
2.2.2 維度分析
利用回歸分析創(chuàng)建因子得分系數(shù)矩陣,如表5所示。
進(jìn)而以因子1得分為橫坐標(biāo),因子2得分為縱坐標(biāo),創(chuàng)建出20款男襯衫樣本的二維象限分布圖,如圖3所示。通過二維象限分布圖可將男襯衫設(shè)計(jì)要素與20個(gè)樣本的感性評(píng)分相對(duì)應(yīng),即根據(jù)樣本最主要的感性意象得分將其分布在對(duì)應(yīng)的二維象限空間中,從而將男襯衫款式設(shè)計(jì)要素與感性意象評(píng)價(jià)的關(guān)聯(lián)度更直觀地體現(xiàn)出來。
分析圖3可知,第1象限的男襯衫款式造型風(fēng)格最為時(shí)尚、前衛(wèi),具有極強(qiáng)的現(xiàn)代感與潮流感,款式特征主要表現(xiàn)為寬松廓形與不對(duì)稱的結(jié)構(gòu)造型設(shè)計(jì);第2象限的男襯衫款式造型風(fēng)格正式、穩(wěn)重,款式較為時(shí)尚,整體廓形較為合體;第3象限的男襯衫款式造型更加經(jīng)典、傳統(tǒng),線條簡單變化少,整體感覺相對(duì)老氣,款式特征主要表現(xiàn)為駁領(lǐng)或立領(lǐng)設(shè)計(jì),整體廓形以合體為主;第4象限的男襯衫款式造型寬松、休閑,整體風(fēng)格表現(xiàn)為活潑且富有朝氣,主要款式特征體現(xiàn)為寬松廓形、連帽領(lǐng)與套頭的穿脫方式等。
3 數(shù)量化理論Ⅰ模型構(gòu)建
3.1 模型構(gòu)建
根據(jù)數(shù)量化理論Ⅰ原理,將設(shè)計(jì)要素設(shè)為項(xiàng)目,設(shè)計(jì)要素子類設(shè)為類目,感性評(píng)價(jià)均值設(shè)為因變量。假設(shè)項(xiàng)目數(shù)量為m,第i個(gè)項(xiàng)目的類目為ri,則δk(i,j)(i=1,2,…,m;j=1,2,…,ri;k=1,2,…,n)表示第k個(gè)樣本中的第i個(gè)項(xiàng)目對(duì)應(yīng)的第j個(gè)類目對(duì)基準(zhǔn)變量y的影響值,如下式所示:
δk(i,j)=1,k樣本中第i個(gè)項(xiàng)目定性數(shù)據(jù)為j類目0,其他(1)
根據(jù)因變量與各項(xiàng)目、類目之間反應(yīng)出的線性關(guān)系,可創(chuàng)建數(shù)學(xué)模型[18]:
yk=∑mi=1∑rij=1δk(i,j)bij+εk(2)
式中:bij表示僅依賴于i項(xiàng)目的j類目的系數(shù);εk為第k次抽樣中的隨機(jī)誤差;ri表示第i個(gè)項(xiàng)目的類目數(shù)[19]。
結(jié)合表1與式(1)得出20款男襯衫樣本反應(yīng)矩陣,如表6所示。
運(yùn)用SPSS 26.0統(tǒng)計(jì)分析軟件,通過多元線性回歸分析求解數(shù)學(xué)模型,對(duì)基準(zhǔn)變量(y)進(jìn)行預(yù)測。本文以因子1(F1)為例,對(duì)無效變量進(jìn)行剔除后,計(jì)算分析得出其類目得分、常數(shù)項(xiàng)、偏相關(guān)系數(shù)、復(fù)相關(guān)系數(shù)與決斷系數(shù)等項(xiàng)目數(shù)值。在多重共線性分析中可知,各類目的方差膨脹因子(VIF)均小于10,說明各自變量之間的共線性現(xiàn)象并不突出,自變量之間的相關(guān)程度符合研究要求,可用于后續(xù)分析[20]。本文以感性因子1為例對(duì)具體線性回歸進(jìn)行分析,結(jié)果如表7所示,其中常數(shù)項(xiàng)為3.216,復(fù)相關(guān)系數(shù)R為0.970,決定系數(shù)R2為0.941。
依據(jù)式(2)建立因子1(F1)預(yù)測模型和因子2(F2)預(yù)測模型,如下式所示:
F1=3.216-2.412A1-1.527A2+0.154B1-0.156B2-0.130B4-0.803C1+0.240D1+0.932D2-0.856E1-0.524E3+0.685F2-1.129G1-0.875G2-0.922H2(3)
F2=2.177-1.363A1-1.267A2-0.623B1-1.045B2+0.524B4-0.794C1-1.131D1+1.275D2+2.948E1-1.112E3-1.385F2+0.040G1+0.713G2-0.205H2(4)
3.2 模型驗(yàn)證
通過計(jì)算可知,感性因子1(F1)復(fù)相關(guān)系數(shù)R=0.970,決定系數(shù)R2=0.941;感性因子2(F2)復(fù)相關(guān)系數(shù)R=0.729;決定系數(shù)R2=0.532;2個(gè)因子的復(fù)相關(guān)系數(shù)R均大于0.5,決定系數(shù)R2均大于0.25,說明2個(gè)因子實(shí)測值與預(yù)測值之間擬合度較高,能夠?qū)Υ蟛糠肿兞窟M(jìn)行解釋。因此,該預(yù)測模型較為理想[21],適用于男襯衫款式設(shè)計(jì)的預(yù)測。
運(yùn)用SPSS 26.0統(tǒng)計(jì)分析軟件做出2個(gè)感性因子的標(biāo)準(zhǔn)化殘差直方圖(圖4)和正態(tài)分布圖(圖5),通過圖4與圖5可知,2個(gè)因子殘差均服從正態(tài)分布,由此說明所創(chuàng)建的預(yù)測模型有效可行。
3.3 實(shí)例驗(yàn)證
某顧客欲訂制一款年輕、休閑風(fēng)格的男襯衫。根據(jù)圖3可知,該風(fēng)格男襯衫主要位于第4象限,表現(xiàn)為寬松廓形、連帽、套頭與弧線底擺等款式特征。綜合上述因素,本文將該男襯衫款式設(shè)計(jì)為圖6所示。
結(jié)合表1分解出該款男襯衫的設(shè)計(jì)要素集合U:
U={A3,B4,C1,D1,E3,F(xiàn)2,G2,H2}
結(jié)合數(shù)量化理論Ⅰ計(jì)算出該款男襯衫設(shè)計(jì)要素反應(yīng)矩陣B為:
B={0,0,1,0,0,0,1,1,0,0,1,0,0,0,0,1,0,1,0,1,0,0,1}
利用因子1(F1)與因子2(F2)預(yù)測模型計(jì)算得出:
F1=3.216-0.130-0.803+0.240-0.524+0.685-0.875-0.922=0.887
F2=2.177+0.524-0.794-1.131-1.112-1.385+0.713-0.205=-1.213
計(jì)算結(jié)果表明,該男襯衫因子得分位于圖3二維象限分布圖的第4象限,款式設(shè)計(jì)要素呈現(xiàn)的造型特征符合年輕、休閑的款式風(fēng)格要求。
在此基礎(chǔ)上,本文采用與前期相同的問卷調(diào)研形式獲取被調(diào)者對(duì)該男襯衫款式造型的感性意象評(píng)分,最終保留有效問卷105份。通過對(duì)問卷數(shù)據(jù)的整理分析后可知,該款男襯衫在“老氣的—年輕的”“正式的—休閑的”感性詞對(duì)中的平均值分別為1.39和1.68,“穩(wěn)重的—活潑的”感性詞對(duì)得分為1.27。上述主觀問卷評(píng)價(jià)結(jié)果均符合消費(fèi)者設(shè)計(jì)需求,并與第4象限男襯衫款式特征相吻合。進(jìn)而結(jié)合該男襯衫款式所有感性詞對(duì)平均分與因子得分通過計(jì)算可知,該款式男襯衫因子1得分為1.781,因子2得分為-0.285,在二維象限分布圖中同樣位于第4象限,與預(yù)測模型計(jì)算結(jié)論相一致。綜上,通過主客觀驗(yàn)證相結(jié)合的方法,從而證明本次預(yù)測模型的有效性與準(zhǔn)確性。
4 結(jié) 論
本文利用感性工學(xué)原理,首先確定研究樣本,并對(duì)研究樣本進(jìn)行感性評(píng)價(jià),將評(píng)價(jià)結(jié)果通過SPSS 26.0軟件進(jìn)行相關(guān)分析后提取感性因子,再通過計(jì)算得出不同樣本在二維象限分布圖中所處的感性意象空間位置,進(jìn)而總結(jié)出各象限男襯衫樣本主要款式與風(fēng)格特征。在此基礎(chǔ)上,利用數(shù)量化理論Ⅰ對(duì)感性研究進(jìn)行客觀驗(yàn)證并得到以下結(jié)論。
1) 利用因子分析法將男襯衫的感性評(píng)價(jià)主要?dú)w納為“氣質(zhì)因子”和“潮流因子”2個(gè)主要影響因子,進(jìn)而創(chuàng)建出男襯衫研究樣本的二維象限分布圖,其中編號(hào)為7#、8#、9#、14#、17#的男襯衫樣本分布于第1象限;編號(hào)為2#、6#、10#、18#的男襯衫樣本分布于第2象限;編號(hào)為4#、12#、13#、16#、19#的男襯衫樣本分布于第3象限;編號(hào)為1#、3#、5#、11#、15#、20#的男襯衫樣本分布于第4象限。
2) 根據(jù)前期收集的男襯衫款式圖,提取男襯衫款式設(shè)計(jì)要素生成反應(yīng)矩陣,利用多元線性回歸分析得出各類目對(duì)感性因子的影響程度并創(chuàng)建回歸預(yù)測模型,最后通過實(shí)例驗(yàn)證,證明該預(yù)測模型能夠?qū)崿F(xiàn)用戶的感性需求與男襯衫款式設(shè)計(jì)要素之間的有效轉(zhuǎn)化,具有較高的可應(yīng)用性。
3) 將感性工學(xué)與數(shù)量化理論Ⅰ相結(jié)合,可以通過數(shù)學(xué)建模的科學(xué)手段對(duì)感性設(shè)計(jì)結(jié)論的正確性進(jìn)行客觀驗(yàn)證,使設(shè)計(jì)師能夠準(zhǔn)確掌握消費(fèi)者感性需求,提高款式設(shè)計(jì)的消費(fèi)者滿意度,最終設(shè)計(jì)出更加符合消費(fèi)者感性需求的服裝。
本文將男襯衫設(shè)定為統(tǒng)一質(zhì)地、純色面料進(jìn)行研究,而服裝的面料、色彩、圖案及配飾等設(shè)計(jì)要素同樣會(huì)對(duì)服裝的造型風(fēng)格產(chǎn)生影響,在后續(xù)研究中,將針對(duì)上述影響因素繼續(xù)進(jìn)行深入研究,并對(duì)已取得的研究成果進(jìn)一步完善,從而彌補(bǔ)本文研究中的不足。
參考文獻(xiàn):
[1]宋瑩. 旗袍個(gè)性定制和展示系統(tǒng)的交互設(shè)計(jì)[J]. 紡織學(xué)報(bào), 2021, 42(4): 144-148.
SONG Ying. Interactive design of cheongsam personalized customization and display system[J]. Journal of Textile Research, 2021, 42(4): 144-148.
[2]高維, 肖軍. 基于女大學(xué)生的服裝設(shè)計(jì)感性評(píng)價(jià)個(gè)體差異[J]. 紡織學(xué)報(bào), 2014, 35(5): 137-141.
GAO Wei, XIAO Jun. Individual differences in perceptual evaluation for fashion design: Taking female students as research subjects[J]. Journal of Textile Research, 2014, 35(5): 137-141.
[3]呂佳, 陳東生. 基于消費(fèi)者心理認(rèn)知的服裝情感評(píng)價(jià)[J]. 紡織學(xué)報(bào), 2015, 36(9): 100-107.
L Jia, CHEN Dongsheng. Evaluation of clothing emotion based on customers psychological cognition[J]. Journal of Textile Research, 2015, 36(9): 100-107.
[4]LI Y F, SHIEH M D, YANG C C. A posterior preference articulation approach to Kansei engineering system for product form design[J]. Research in Engineering Design, 2019, 30(1): 3-19.
[5]于小利. 基于感性意象的服裝網(wǎng)店設(shè)計(jì)研究[J]. 絲綢, 2016, 53(7): 43-48.
YU Xiaoli. Research on online clothing store design based on Kansei image[J]. Journal of Silk, 2016, 53(7): 43-48.
[6]WU F G, YU C Z. Parametric design and Kansei engineering in goblet styling design[J]. Mathematical Problems in Engineering, 2020(10): 1-8.
[7]JIN M Y, SUN Y C. Chinese Gen Zs emotional dimensions for fashion design during the pandemic[J/OL]. International Journal of Fashion Design, Technology and Education, 2022, DOI: 10.1080/17543266.2022.2126897.
[8]GE B, SHAARI N. Optimize the online shopping title of mens plain-color shirts in e-commerce based on Kansei engineering[J]. Journal of Global Fashion Marketing, 2022, 13(2): 1-17.
[9]CHEN D L, CHENG P P. Development of design system for product pattern design based on Kansei engineering and BP neural network[J]. International Journal of Clothing Science and Technology, 2022, 34(3): 335-346.
[10]XUE L, YI X, ZHANG Y. Research on optimized product image design integrated decision system based on Kansei engineering[J]. Applied Sciences, 2020, 10(4): 90-98.
[11]于娜, 張聰, 杜游, 等. 基于數(shù)量化理論的家具造型意象設(shè)計(jì)[J]. 包裝工程, 2018, 39(22): 183-188.
YU Na, ZHANG Cong, DU You, et al. Furniture modeling image design based on quantitative theory[J]. Packaging Engineering, 2018, 39(22): 183-188.
[12]劉婕羽, 江影. 運(yùn)動(dòng)內(nèi)衣后背款式設(shè)計(jì)的感性評(píng)價(jià)[J]. 針織工業(yè), 2019(7): 64-68.
LIU Jieyu, JIANG Ying. Perceptual evaluation of back style design of sports underwear[J]. Knitting Industries, 2019(7): 64-68.
[13]FANG F, HU C L, YAN T T. Research on bra component design and perceptual image prediction[J]. International Journal of Clothing Science and Technology, 2021, 33(5): 744-757.
[14]李倩文, 王建萍, 楊雅嵐, 等. 基于數(shù)量化理論Ⅰ的男西裝款式要素感性評(píng)價(jià)[J]. 紡織學(xué)報(bào), 2021, 42(5): 155-161.
LI Qianwen, WANG Jianping, YANG Yalan, et al. Perceptual evaluation of mens suit style elements based on quantitative theory Ⅰ[J]. Journal of Textile Research, 2021, 42(5): 155-161.
[15]于欣禾, 王建萍. 互聯(lián)網(wǎng)環(huán)境下男襯衫定制顧客感知價(jià)值評(píng)價(jià)方法[J]. 紡織學(xué)報(bào), 2020, 41(3): 136-142.
YU Xinhe, WANG Jianping. Customer perceived value evaluation method of mens shirts customization under internet environment[J]. Journal of Textile Research, 2020, 41(3): 136-142.
[16]宋瑩, 王寶環(huán), 溫蘭. 基于感性工學(xué)的針織服裝領(lǐng)型設(shè)計(jì)[J]. 針織工業(yè), 2017(10): 58-61.
SONG Ying, WANG Baohuan, WEN Lan. Kansei engineering based on collar design of knitting apparel[J]. Knitting Industries, 2017(10): 58-61.
[17]郭冰潔, 薛媛. 旗袍領(lǐng)型與開襟的感性評(píng)價(jià)研究[J]. 西安工程大學(xué)學(xué)報(bào), 2017, 31(3): 338-344.
GUO Bingjie, XUE Yuan. Emotional evaluation of cheongsams collar shapes and open fronts[J]. Journal of Xian Polytechnic University, 2017, 31(3): 338-344.
[18]李明珠, 何燦群, 盧章平, 等. 基于數(shù)量化理論Ⅰ類的汽車意象造型設(shè)計(jì)研究[J]. 機(jī)械設(shè)計(jì), 2016, 33(4): 105-108.
LI Mingzhu, HE Canqun, LU Zhangping, et al. Research on car image modeling design based on quantification theory type Ⅰ[J]. Journal of Machine Design, 2016, 33(4): 105-108.
[19]時(shí)倩穎, 王曉妍. 基于數(shù)量化理論的民國女性形象商標(biāo)意象研究[J]. 包裝工程, 2022, 43(6): 374-381.
SHI Qianying, WANG Xiaoyan. Trademark image of female image in the Republic of China based on quantification theory[J]. Packaging Engineering, 2022, 43(6): 374-381.
[20]陳偉偉. 基于感性匹配的服裝協(xié)同設(shè)計(jì)原理及應(yīng)用: 以女裙裝為例[D]. 蘇州: 蘇州大學(xué), 2018.
CHEN Weiwei. The Principle and Application of Garment Collaborative Design Based on Perceptual Matching: Take Female Dresses as an Example[D]. Suzhou: Soochow University, 2018.
[21]周俊, 李永鋒, 朱麗萍. 基于數(shù)量化理論Ⅰ的老年人APP用戶體驗(yàn)設(shè)計(jì)[J]. 包裝工程, 2018, 39(22): 251-257.
ZHOU Jun, LI Yongfeng, ZHU Liping. APP user experience design for the elderly based on quantification theory Ⅰ[J]. Packaging Engineering, 2018, 39(22): 251-257.
Perceptual evaluation of mens shirt design based on quantitative theory Ⅰ
SONG Ying, RUAN Shengkun
(College of Clothing and Textile, Eastern Liaoning University College, Dandong 118000, China)
Abstract:
Mens shirts have a high universality in daily life and are a kind of clothing commonly seen by the public. With the development and progress of the clothing industry, this kind of clothing has gradually formed its own unique design language. At the same time, with the improvement of consumers personalized requirements for clothing, homogenous and imitative style design can no longer meet the dressing demand of todays consumer groups for mens shirts. Therefore, in the process of fashion design, only designers who fully consider the emotional needs of users can design clothing products that meet consumer satisfaction and make consumers satisfied. In view of this situation, we take mens shirts as the research object and put forward a style design research scheme combining Kansei engineering and quantitation theory Ⅰ.
First of all, we collect and determine the research samples of mens shirts and the perceptual word pairs of adjectives that can accurately express the style and shape of mens shirts. In this paper, in order to ensure that the follow-up evaluation of the male shirt style by the consumer group is free from the interference of various factors such as fabric texture, pattern, color, accessories and models, we draw black-and-white line drawings of the research samples in the same proportion in order to eliminate these interference factors, which will be used as the stimulus diagram for the follow-up study. Next, we use the product semantic difference method that consists of five perceived magnitudes to create a perceptual questionnaire, so that the respondents can evaluate it in the form of a score, with reference to the degree of fit between the style of a sample of mens shirts and eight pairs of perceptual words, and not only that, we need to use SPSS software to analyze the evaluation results. By using principal component analysis to extract the common factors from the factor analysis, we finally categorize the sources of the respondents perceptions of mens shirts into two main influencing factors, namely the “temperament factor” and the “trend factor”. On this basis, we use regression analysis to create factor score coefficient matrix, and create two-dimensional quadrant distribution space of mens shirts. Through two-dimensional quadrant distribution map, the design elements of mens shirts can be corresponding to the perceptual score of the research samples. That is, according to the most important perceptual image score of the samples, the design elements of mens shirts and perceptual scores of research samples are distributed in the corresponding two-dimensional quadrant space, so as to reflect the correlation between the design elements of mens shirts and the perceptual imagery ratings more intuitively. At the same time, we analyze the style characteristics of mens shirts and summarize the main design elements of mens shirts, and refine the main design elements of mens shirt styles into eight elements, and 23 sub-categories of elements. In addition, we apply quantitation theory Ⅰ to create reflective matrices of mens shirt style design elements, and through linear regression analysis, the correlation between perceptual factors and design elements is predicted, and a predictive mathematical model is constructed. Through correlation analysis, it can be seen that the mathematical prediction model has a high degree of fitting between the measured values and the predicted values, which meets the requirements of normal distribution and can explain most variables. Therefore, the prediction model is ideal, effective and feasible, and has high scientific and universality. Finally, through the design and verification of practical cases, it is further proved that in the process of clothing style design, combining Kansei engineering with quantitative theory Ⅰ can realize the effective integration and transformation between users perceptual needs and clothing design elements, help designers accurately grasp users psychological needs, and design and develop products that can better meet consumers psychological needs.
In this study, the mens shirt is set as a uniform texture, the same solid colour fabric for research, while the design elements of the fabric, colour, pattern and accessories will also have an impact on the style of the garment. In the subsequent research, we will continue to conduct in-depth research on the above-mentioned influencing factors, and further improve the research results achieved, so as to make up for the shortcomings in this study.
Key words:
mens shirt; Kansei engineering; style design; quantitative theory; design elements; mathematical model
收稿日期:
2022-07-20;
修回日期:
2023-01-23
基金項(xiàng)目:
作者簡介:
宋瑩(1973),女,副教授,主要從事服裝設(shè)計(jì)與工程的研究。